" Project name : DelPhi Project home page : e.g. http://compbio.clemson.edu/delphi.php Operating system ( s ) : Linux , Mac , Windows Programming language : Fortran and C Other requirements : no License : free of charge license is required Any restrictions to use by non - academics : Commercial users should contact Accelrys Inc . "
We have developed ANDES , a software library and a suite of applications , written in Perl and R , for the statistical ANalyses of DEep Sequencing .
" Project name : ANDES Project home page : http://andestools.sourceforge.net/ Download web site : https://sourceforge.net/projects/andestools Operating system : Tested and in production on Linux . Programming language : Perl and R License : GNU GPL V 3 Any restrictions to use by non - academics : none "
The MAFCO compression tool can be found at : http://bioinformatics.ua.pt/software/mafco ; https://github.com/lumiratos/mafco .
PyPhi is open - source and licensed under the GPLv 3 ; the source code is hosted on GitHub at https://github.com/wmayner/pyphi .
CoXpress is written in the native R language and has been fully tested on both windows and linux .
" • Project Name : coXpress • Project Home Page : http://coxpress.sf.net • Operating Systems : Windows , Linux • Programming Language : R • Other Requirements : R , gplots , gtools , gdata ( for heatmaps ) , hu 6800 , hgu 95av 2 , plotrix ( for examples ) • License : GNU GPL "
CloVR - ITS is made available as a pre - installed , automated , and portable software pipeline for cloud - friendly execution as part of the CloVR virtual machine package ( http://clovr.org ) .
The library , called ENCORE ( http://encore-similarity.github.io/encore ) , interfaces with the MDAnalysis molecular analysis toolkit [14] and can be used both as a Python library and from the command line .
ENCORE is freely available ( http://encore-similarity.github.io/encore ) , together with its documentation and several examples on how to use it , and is distributed under the GNU general public license , version 3 .
Users are welcome to use an instance of PhyloBot available at http://www.phylobot.com , or launch their own instance of PhyloBot using its open - source code .
PhyloBot is available to use at http://www.phylobot.com , and its source code is available at https://github.com/vhsvhs/phylobot-django .
In this paper , we have chosen to extend the use of an individual atlas to multiple atlases in a recently introduced , fully automated , feature - based nonlinear labeling method called Mindboggle ( freely downloadable , open source Matlab code ) [63,85] .
Mindboggle is a freely downloadable , open source software package written in Matlab ( version 6 , release 13 , with the Image Processing Toolbox , The Mathworks Inc . , USA ) and has been tested on different models of desktop and laptop computers running different distributions of Linux , as well as MacOSX and Windows .
We have developed the HMMER web site ( http://hmmer.janelia.org ) to not only provide downloadable HMMER binaries , documentation and source code as it has done in the past , but now also to provide an interface for performing protein sequence searches with near interactive response times .
To this end , we developed scPipe , an R / Bioconductor package that integrates barcode demultiplexing , read alignment , UMI - aware gene - level quantification and quality control of raw sequencing data generated by multiple protocols that include CEL - seq , MARS - seq , Chromium 10X , Drop - seq and Smart - seq .
The scPipe R package is available for download from https://www.bioconductor.org/packages/scPipe .
scPipe is an R [13] / Bioconductor [14] package that can handle data generated from all popular 3 ’ end scRNA - seq protocols and their variants , such as CEL - seq , MARS - seq , Chromium 10X and Drop - seq .
The scPipe package is written in R and C + + and uses the Rcpp package [ 16 , 17 ] to wrap the C + + code into R functions and the Rhtslib package [18] for BAM input / output .
• Methods and Results : MatrixConverter is an open source program written in Java ; a platform - independent binary executable , as well as sample data sets and a user ’ s manual , are available at https://github.com/gburleigh/MatrixConverter/tree/master/distribution .
iDREM is implemented using a combination of Java and Javascript .
The iDREM code and software , with an example input dataset and detailed instructions are available from GitHub ( https://github.com/phoenixding/idrem ) .
All programs included in the PoreWalker pipeline are developed in - house in C and PERL programming languages .
VASP - E was developed in ansi C / C + + using gcc ( the Gnu Compiler Collection ) version 4.4.7 , on 64 bit linux - based computing platforms .
A random set of 50 leaves were scanned and analysed using ImageJ [20] and LAMINA .
" Project name : LAMINA : Leaf shApe deterMINAtion Project home page : http://sourceforge.net/projects/lamina Operating system ( s ) : Platform independent Programming language : Java Other requirements : Java 1.4 .x or higher .
LAMINA uses the Java Advanced Imaging ( JAI ) package http://java.sun.com/javase/technologies/desktop/media/jai/ to support common image file formats , which is bundled with the installation and hence no additional installation should be required .
Then we developed MSACompro , a new multiple sequence alignment method , which effectively utilizes predicted secondary structure , relative solvent accessibility , and residue - residue contact map together with posterior alignment probabilities produced by both pair hidden Markov models and partition function as in MSAProbs [4] .
SCOTTI is distributed as an open source package for the phylogenetic software BEAST 2 .
SCOTTI is implemented as an open - source package for the Bayesian phylogenetic software BEAST 2 [28] , and as such , it can be freely installed and used .
Availability : FunciSNP is available from Bioconductor ( bioconductor.org ) .
FunciSNP is an R package , which is licensed under the General Public License ( GPLv 3 ) and is freely available through the Bioconductor repository ( [31] ) .
We developed V - Phaser 2 , a publicly available software tool ( V - Phaser 2 can be accessed via : http://www.broadinstitute.org/scientific-community/science/projects/viral-genomics/v-phaser-2 and is freely available for academic use ) that enables the efficient analysis of ultra - deep sequencing data produced by common next generation sequencing platforms for viral populations .
We developed the V - Phaser 2 program that overcomes these limitations of V - Phaser [12] .
The source code of LAILAPS - QSM is available under GNU General Public License version 2 in Bitbucket GIT repository : https://bitbucket.org/ipk_bit_team/bioescorte-suggestion
An R package for T3 _ MM is freely downloadable from : http://biocomputer.bio.cuhk.edu.hk/softwares/T3_MM .
Project name : PyMS Project home page : http://code.google.com/p/pyms/ Operating system ( s ) : Platform independent Programming language : Python Other requirements : NumPy , Netcdf , Pycdf , Pycluster , matplotlib , tcl , tk License : GNU GPL 2 Any restrictions to use by non - academics : No "
The PhysiCell source code , examples , documentation , and support are available under the BSD license at http://PhysiCell.MathCancer.org and http://PhysiCell.sf.net .
We have tested PhysiCell on Windows through MinGW - w64 , and on OSX and Linux via g + + .
Then browsing a recent release directory ( e.g. , PhysiCell 1.2.2 ) , and downloading the ova file . https://github.com/MathCancer/PhysiCell/releases/latest
As open - source software , the dcGOR package is freely available under the GPL - 2 license ( see Software S1 ) .
For ease of installation ( R package dependencies ) , it is distributed as part of CRAN , http://cran.r-project.org/package=dcGOR .
For ease of version control , it is also distributed at GitHub , https://github.com/hfang-bristol/dcGOR .
This classification module was incorporated into our karyotyping software tool , called MetaSel , which was written from scratch using C # on Microsoft Windows 7 operating system .
Both software ( for Windows XP or 7 only ) and user manual can be freely downloaded from our website , http://www4a.biotec.or.th/GI/tools/metasel .
The OpenSim software is covered by the Apache License 2.0 , which permits its use for any purpose including both nonprofit and commercial applications .
The OpenSim source code is available under the permissive Apache License 2.0 , making OpenSim suitable for any academic , commercial , government , or personal use ( some dependencies have more restrictive licenses ) .
The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware .
NeuroMap is made freely available to the community under GNU General Public License ( GPL ) at http://sites.google.com/site/neuromapsoftware .
NeuroMap is licensed under GNU GPL and can be freely downloaded from a dedicated website ( http://sites.google.com/site/neuromapsoftware ) .
The first generation Bayesian Evolutionary Analysis by Sampling Trees ( BEAST ) package [1] , [2] has become a popular platform for solving such problems and takes a modeling philosophy that all of these evolutionary analysis problems share at their core one or more phylogenetic time - trees .
This paper describes the overarching design and implementation details of a re - write of the BEAST platform that we have designated BEAST 2 , as well as presenting examples of some significant new models developed especially for this new platform .
The BEAST 2 platform is an open source project and is anonymously available on a source repository hosted by GitHub at https://github.com/CompEvol/beast2 and supplementary material Code S1 .
This example file runs on BEAST 2.1.0 with the MultiTypeTree package ( http://compevol.github.io/MultiTypeTree/ ) .
The pSSAlib source code and pre - packaged installers are freely available from mosaic.mpi - cbg.de as open source under the GNU LGPL v 3 license .
Wham and all associated software are covered under the MIT License and can be freely downloaded from github ( https://github.com/zeeev/wham ) , with documentation on a wiki ( http://zeeev.github.io/wham/ ) .
Wham and all associated software can be found on github ( https://github.com/zeeev/wham ) , documentation is on the wiki ( http://zeeev.github.io/wham/ ) .
Telescope is implemented in Python , is available as an open - source program under the MIT license , and has been developed and tested on Linux and MacOS .
Pep2Path is freely available from http://pep2path.sourceforge.net/ , implemented in Python , licensed under the GNU General Public License v 3 and supported on MS Windows , Linux and Mac OS X .
AccuTyping takes inputs of the two color intensities digitized from scanned microarray images with one of the two popular software packages , GenePix ( Axon Instrument , Union City , CA ) or ImaGene ( Biodiscovery , Inc . , El Segundo , CA ) .
The DOGS software was implemented in the programming language Java ( Oracle Corporation , 500 Oracle Parkway , Redwood Shores , CA 94065 , USA ) version 1.6 and uses the Chemistry Development Kit ( CDK , version 1.0.2 ) [23] , [24] .
Additionally , PathVisio 3 introduces a new powerful extension systems that allows other developers to contribute additional functionality in form of plugins without changing the core application.PathVisio can be downloaded from http://www.pathvisio.org and in 2014 PathVisio 3 has been downloaded over 5,500 times .
PathVisio is a freely available , open - source tool published under the Apache 2.0 license ( http://www.apache.org/licenses/LICENSE-2.0 ) .
To enable the integration of PathVisio in an automated workflow , we developed PathVisioRPC ( http://projects.bigcat.unimaas.nl/pathvisiorpc/ ) to be able to call PathVisio from other programming languages through an XML - RPC server .
THREaD Mapper Studio is mostly coded in Python and JavaScript .
Availability : The package is freely available under LGPL from the R - Forge web site ( http://repitools.r-forge.r-project.org/ )
More details : Software name : CBFA plugin for Optflux Project home page : http://www.optflux.org/ Methods details and application tutorial : http://www.optflux.org/cbfa Operating system ( s ) : Platform independent Programming languages : Java Other requirements : Java JRE 1.7 .x ( for Mac OS users the installation of JDK 1.7 is recommended ) , GLPK License : GNU - GPL , version 3 "
" • Project name : SSPACE - LongRead • Project home page : http://www.baseclear.com/bioinformatics-tools/ • Operating systems : All major Linux platforms • Programming languages : Perl , C + + ( the latter is required for BLASR , see below ) • Other requirements : BLASR for the alignment of long reads [22] • License : BaseTools software license • Any restrictions to use by non - academics : commercial licence needed "
A second major version of CellProfiler , rewritten in Python from its original MATLAB implementation , was published in 2011 [5] and included methods for tracking cells in movies and measuring neurons , worms , and tissue samples .
In the CellProfiler 3.0 release , we introduced methods for analyzing 3D images , using deep learning architectures and cloud computing resources , and other improvements to CellProfiler ’ s usability and capabilities .
( B ) Evaluation of CellProfiler 3.0 performance in comparison to the MorphoLibJ plugin in Fiji software .
The web service [44] available at http://www.fragit.org enables users to upload their structure , fragment it and download the resulting input file to GAMESS .
The FragIt source code is distributed under an open source license ( GPL , version 2 or later ) and users of the FragIt code are encouraged to submit changes and additions , especially for their own ( fragmentation ) methods .
In contrast to the original tool , ggsashimi internally generates an R script which uses the ggplot 2 library [5] for the graphical rendering .
Since ggsashimi uses the most popular file formats and has very few dependencies , it can be easily integrated in any splicing analysis pipeline , and can facilitate the interrogation of alternative splicing in large - scale RNA sequencing projects , such as ENCODE [6] and GTEx [7] . ggsashimi is freely available at https://github.com/guigolab/ggsashimi .
Our software has been developed and tested on Windows , Mac , and Linux platforms and is available publicly under an open source BSD license ( https://github.com/krm15/ACME ) .
The stable release version of sourceR is available from the Comprehensive R Archive Network , released under a GPL - 3 licence .
Podbat is open source software freely downloadable from www.podbat.org , distributed under the GNU LGPL license .
Podbat requires Java version 1.6 or higher .
Podbat is open source software implemented as a desktop application in Java and can be freely and anonymously downloaded from www.podbat.org or as supplemental material accompanying this paper ( Software S1 ) .
The software and documentation for M - Track is freely available for download from the Scimemi Lab website ( https://sites.google.com/site/scimemilab2013/software ) or from the GitHub repository , which also includes detailed instructions on software installation and video analysis , which can be tested in videos of black and white mice ( https://github.com/scimemia/M-Track ) .
M - Track was written using Python 2.7 , OpenCV 3.0 and Qt 4.8 , which can be downloaded free of charge at the URLs reported in Table 3 .
The software and documentation for M - Track are freely available for download from the Scimemi lab website ( https://sites.google.com/site/scimemilab2013/software ) or from the GitHub repository ( https://github.com/scimemia/M-Track ) .
VDJtools is an open - source software , the source code can be accessed at GitHub [40] .
OHM ( OligoHeatMap ) is an online tool able to provide estimates of T for a set of oligomers and a set of aligned sequences , not only as text files of complete results but also in a graphical way : T values are translated into colors and displayed as a heat map image , either stand alone or to be used by softwares such as TreeDyn to be included in a phylogenetic tree .
AVAILABILITY : QuIN ’ s web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript , utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV 3 license available on GitHub : https://github.com/UcarLab/QuIN/ .
To overcome the limitations of current tools , we developed a single platform for Querying and visualizing Chromatin Interaction Networks ( QuIN ) ( http://quin.jax.org ) ( Fig 1 ) .
QuIN is an open source project released under the GNU General Public License Version 3 and is available on GitHub ( https://github.com/UcarLab/QuIN/ ) and in S1 software .
MicroSyn is now implemented in C # on Windows platform .
" Project name : MicroSyn Project home page : http://fcsb.njau.edu.cn/microsyn Operating system ( s ) : Windows Programming language : C # Requirements : .net framework on Windows "
Availability : ProDy is open source and freely available under GNU General Public License from http://www.csb.pitt.edu/ProDy/ .
Implementation illuminaio is an R package [9] .
Software availability illuminaio is an R package available from the Bioconductor project ( http://www.bioconductor.org ) and from http://dx.doi.org/10.5281/zenodo.7588 .
We present ASPASIA ( Automated Simulation Parameter Alteration and SensItivity Analysis ) , a cross - platform , open - source Java toolkit that addresses a key deficiency in software tools for understanding the impact an intervention has on system behaviour for models specified in Systems Biology Markup Language ( SBML ) .
ASPASIA , released under the Artistic License ( 2.0 ) , can be downloaded from http://www.york.ac.uk/ycil/software .
ASPASIA is open source and available under the Artistic License ( 2.0 ) .
MAGPIE was implemented in Ruby on Rails 5 .
The MAGPIE source code can be downloaded from the GitHub repository at https://github.com/christbald/magpie and installed on any public or private server , as well as on any local computer .
To address this need , we propose a novel reactive coarse - grained force field , as well as a publicly available software package , named the Mechanochemical Dynamics of Active Networks ( MEDYAN ) , for simulating active network evolution and dynamics ( available at www.medyan.org ) .
Here , we present a novel Python - based toolbox called HDDM ( hierarchical drift diffusion model ) , which allows fast and flexible estimation of the the drift - diffusion model and the related linear ballistic accumulator model .
Availability and implementation : See www.genepattern.org to run online , or www.broadinstitute.org/rna-seqc/ for a command line tool .
We implemented CNVkit as a Python 2.7 software package comprising a command - line program , cnvkit.py , and reusable library , cnvlib .
CNVkit generates several kinds of plots using the software libraries Biopython [35] , Reportlab ( http://www.reportlab.com/opensource/ ) and matplotlib ( http://matplotlib.org ) :
CNVkit source code is freely available from https://github.com/etal/cnvkit under the Apache License 2.0 ( http://www.apache.org/licenses/LICENSE-2.0 ) .
To facilitate the simultaneous analysis and comparison of multiple HTP experiments in the context of biological pathways and association networks , and allow pattern extraction of a selected gene list with biological themes , we developed a stand - alone , Windows - based software tool called WholePathwayScope , or WPS .
" Project name : Pathway analysis tool WPS for high - throughput data ; Project home page : http://www.abcc.ncifcrf.gov/wps/wps_index.php [63] Operating system : Microsoft Window 2000 or XP Programming language : Microsoft Visual Basic 6 Other requirements : Internal databases for different species and a collection of over 1900 PathwayScopeFiles ( PSCP files for mouse ) available on web site ; Additional user - provided PSCP files and those from other sources will be made available as they are collected .
" Project name : NemaFootPrinter Project home page : http://bio.ifom-firc.it/NTFootPrinter/index.html server side : UNIX type platforms client side : Any operating system Programming language : SQL , Perl , Java Other requirements : The web - based application was tested and is compatible with the more common Internet browser .
SNPdetector runs on Unix / Linux platform and is available publicly ( http://lpg.nci.nih.gov ) .
To compare the performance of SNPdetector with the other SNP detection programs , we reanalyzed a subset of ENCODE data ( 61 amplicons on Chromosome 18 ) using PolyPhred 5.0.2 and NovoSNP [17] ( a new SNP detection software package ) .
SNPdetector runs on Unix and Linux and is publicly available by anonymous ftp ( http://lpg.nci.nih.gov ) .
SNPdetector was implemented in C and Perl .
MIiSR natively supports positions files from Leica GSD - SR Ground - State Depletion microscopes , Zeiss ELYRA PS 1 dSTORM microscopes , and any microscope running QuickPALM software [34] .
MIiSR is an open - source project licensed under the GNU General Public License and is available as S1 - MIiSR Program in this paper , with updated versions published at http://www.phagocytes.ca/miisr/ .
MIiSR works on any Linux , Windows and Macintosh computer running an appropriate version of Matlab equipped with the image processing , statistics and parallel processing toolboxes .
" Project name : GenomePop v. 1.0 Project home page : http://webs.uvigo.es/acraaj/GenomePop.htm Operating system ( s ) : Windows and Linux ( the source will be provided to compile for Mac ) Programming language : C + + License : GNU GPL . "
" • Project name : 3C Primer Design • Project home page : http://www.pristionchus.org/3CPrimerDesign/ • Operating system ( s ) : Platform independent • Programming language : Java • Other requirements : Any web browser supporting forms • License : The web interface is freely available to academic users • Any restrictions to use by non - academics : Licence needed "
The different software packages , including a server - indepenent version as well as a web server for Windows and Linux based systems , are available at http://code.google.com/p/biographer/ under the open - source license LGPL .
Software for GINI is available at http://sailing.cs.cmu.edu/Drosophila_ISH_images/ ( b ) GINI extends such analysis to inferring a network from bags of images per gene .
" Project name : ProteoLens • Project home page : http://bio.informatics.iupui.edu/proteolens/ • Operating system ( s ) : The software is platform independent and can run anywhere Java Virtual Machine runtime is available .
An installer is provided for Windows NT / XP / 2003 / Vista users .
• Programming language : Java • Other requirements : Java Runtime Environment ( JRE ) version 1.5 or above is required .
aLFQ is written in R and freely available under the GPLv 3 from CRAN ( http://www.cran.r-project.org ) .
VBA ' s code is under open - source GNU General Public Licence ( v 2 ) , and is freely downloadable from the toolbox ' s internet wiki pages ( http://code.google.com/p/mbb-vb-toolbox/wiki/InstallingTheToolbox ) .
MAGERI is implemented in Java v 1.8 and is distributed as a single cross - platform executable JAR file [ https://github.com/mikessh/mageri ] .
Ensembler is free and open source software licensed under the GNU General Public License ( GPL ) v 2 .
Ensembler is written in Python , and can be used via a command - line tool ( ensembler ) or via a flexible Python API to allow integration of its components into other applications .
The code for Ensembler is hosted on the collaborative open source software development platform GitHub ( github.com / choderalab / ensembler ) .
CGBayesNets is implemented in MATLAB and available as MATLAB source code , under an Open Source license and anonymous download at http://www.cgbayesnets.com .
The collected data were coded and entered into epidata software version 3.1 and exported to SPSS V - 20 for analysis .
The heartbeat perception task was programmed using E - Prime 2.0 software ( http://www.pstnet.com/products/e-prime/ ) and presented on a 19 - inch CRT monitor with 640x 480 screen resolution and a 60 Hz refresh rate .
Upon reaching adulthood , individuals were photographed and their head width and pronotum width measured to the nearest 0.01cm using ImageJ 1.48 [45] , with sex being determined by examination of the sexually dimorphic subgenital plates .
Models were built in the R environment [50] using the nlme package [51] .
All structure images were created using DS ViewerPro 6.0 [42] .
Microsoft Excel 2007 was used to compile the data and STATA Version 12.0 was used for statistical analyses [28] .
Significance was accepted at P ≤ 0.05 , statistical power was 90 % , and the analyses were performed in Statistical Package for Social Sciences version 20.0 ( SPSS , Chicago , Illinois , USA ) .
Quantitative data were recorded by interviewers on data sheets , double entered in Epi Info 3.5.1 ( CDC , Atlanta , GA , USA ) by data entry clerks and cleaned for statistical analysis in SAS 9.2 ( SAS Institute , Cary , NC , USA ) .
This enabled automatic importation of entire interviews with codes into the qualitative data analysis software MAXQDA 10 ( VERBI Software , Consult . Sozialforschung . GmbH , Marburg , Germany ) .
In this study , we implemented QRFs by R package “ quantregForest ” ( version 0.2 - 3 ) and assessed the variable importance by permutation used in the original random forest algorithm .
The analyses were done using SAS ( Version 9.1.3 . SAS Institute Inc . , Cary , NC , USA ) .
Statistical analysis was conducted with Statistical Package for Social Sciences version 15.0 software ( SPSS inc . , Chicago IL , USA ) and figures were constructed with GraphPad Prism 5 software ( GraphPad Software inc . , La Jolla CA , USA ) .
Cortical reconstruction and volumetric segmentation of each subject ’ s T1 image to produce an ROI atlas was performed using the FreeSurfer image analysis suite [17] , available online at http://surfer.nmr.mgh.harvard.edu .
The DWI ' s were preprocessed using AFNI and FSL tools [18] .
The network extraction step of the “ Statistical Analysis of Minimum cost path based Structural Connectivity ” ( SAMSCo ) framework [4] was used to define structural connectivity because it minimizes the influence of directional uncertainty while finding globally optimal paths .
Preprocessing of the fMRI ' s was accomplished using ANFI and FSL tools [18,19] .
Amplified DNA was analyzed for length variations on an ABI 3700 sequencer using GENEMAPPER 4.0 ( Applied Biosystems ) .
Mitochondrial and nuclear DNA analysis : Sequences were aligned in BIOEDIT 7.0.9.0 [32] using the ClustalW algorithm .
Haplotypes were identified using ARLEQUIN 3.11 [33] .
For nuclear sequences , two alignments were created : first , heterozygous sites were coded using the IUPAC ambiguity codes ( unphased dataset ) ; and second , gametic phases of nuclear sequences were inferred using the Bayesian algorithm implemented in PHASE 2.1 [34] ( phased dataset ) .
Recombination in our nuclear genes was tested using the PHI test implemented in SPLITSTREE 4.11.3 [35] and the tree - based SBP and GARD methods [36] implemented online via the Datamonkey webserver [37] .
The most suitable model of DNA substitution for each locus and dataset was determined using MODELTEST 3.0 [38] according to the Akaike Information Criterion ( AIC ) .
PhyML 3.0 [39] was used to perform ML analyses with default parameters as starting values .
Bayesian analyses were performed with MRBAYES 3.1.1 . [40] .
A 50 % Majority - rule consensus tree was generated in PAUP 4.0b 10 [41] .
Median joining networks were performed with NETWORK 4.5.1.6 [42] to explore relationships among haplotypes for the mitochondrial ( cytb / COI ) and nuclear ( bfibr / G6pd ) datasets .
Tables of nuclear allele frequency were computed with GENEPOP 4.0.11 [43] and frequency differences ( genic differentiation ) were tested for each nuclear locus and across all nuclear loci for all pairs of lineages containing more than three individuals with GENEPOP .
The net genetic distance between lineages was computed in MEGA 4.1 [44] under the Kimura two parameters ( K2P model ) for the cytb dataset .
Divergence times of L . neilli and L . edwardsi , and of the main lineages of L . neilli ( approximation of the time to the most recent common ancestor - TMRCA [45] , ) , were estimated using Bayesian inference , as implemented in the program BEAST 1.6.1 [46] on the cytb dataset .
Convergence of the chains to the stationary distribution was checked using TRACER 1.5 [54] .
All BEAST computations were performed on the computational resource Bioportal at the University of Oslo ( http://www.bioportal.uio.no ) .
The allelic richness ( AR ) was calculated using the rarefaction procedure implemented in FSTAT 2.9.3.2 [55] .
The proportion of null alleles ( NA ) at each locus and for each population was estimated with FREENA [56] and genotypes were corrected using MICRO - CHECKER 2.2.3 [57] .
STRUCTURE 2.3.1 [58] was used to infer the number of populations ( K ) and assign individuals to genetic clusters independently of spatial sampling .
We used CLUMPP 1.1 [59] to average the results of multiple iterations for a given K .
GENELAND 3.3.0 [60] was used to perform a spatial genetic analysis by integrating geographic and genetic information and to determine the most probable K .
A visual output of the STRUCTURE and GENELAND results was generated using DISTRUCT [61] .
IBD among the four groups of populations and within groups including at least four clusters ( northeast and west ) was tested by comparing pairwise geographic distance ( log transformed ) with pairwise ( FST / [ 1 − FST ] ) and ( RST / [ 1 − RST ] ) using ARLEQUIN and SPAGeDI 1.3 [62] , respectively .
We used VIP ( Vicariance Inference Program ) [63] to localize the main isolating barriers within L . neilli distribution range .
Approximate Bayesian computation implemented in the software DIYABC 1.0.4.45beta [66] was used to infer the evolutionary history of L . neilli combining our mitochondrial and microsatellite datasets .
We performed a maximum likelihood land cover classification using ENVI ( Environment for Visualizing Images ) software ( ITT 2011 ) [40] .
4 , 2010 from Digital Globe , Inc . Spatial analysis was performed utilizing geo - spatial modeling environment ( GME ) software version 0.5.8 beta [41] and Fragstats software version 3.3 [42] .
Individual and environmental risk factors for Lyme disease : We used general estimating equation models ( XTGEE ) in STATA / SE , version 12.0 ( STATA Corporation , College Station , TX ) to assess the association between personal protective behaviors , age , landscape metrics and individual serological status .
Statistical analysis was performed using the software package SPSS Statistics 24.0.0.0 ( IBM Corp . Armonk , NY , USA ) and statistical significance was defined as p < 0.05 .
Data were entered in EpiData version 3.1 ( " The EpiData Association " Odense , Denmark ) and exported to STATA version 12 ( StataCorp , College Station , Texas 77845 USA ) for analysis . Analysis was by intention - to - treat whereby participants were kept in the groups in which they were randomised and final analysis excluded those with ‘ missing of data ’ about outcomes of interest ( lost to follow up , had abortions ) [29] .
The experimental programs were written and operated with Microsoft ™ Visual Basic ™ 2010 software ( Microsoft Corp . ; Redmond , WA , USA ) .
The original pictures were manipulated using Adobe Photoshop software ( Adobe Systems ; San Jose , CA , USA ) and Pixelmator ( Pixelmator Team Ltd . ; Vilnius , Lithuania ) .
Data were analysed using a generalised linear mixed model ( GLMM ) in R 3.3.1 [37] using the lme 4 package [38] .
Spatial analysis was integrated using geographic information system software ( GIS 10 ) .
From these images , ray 4 and ray 6 were measured to the nearest 0.001 mm using Motic Digilab II ( Motic Instruments Inc . , Hong Kong ) .
All analyses were performed using the SAS GLM procedure ( Version 9.3 ; SAS Institute , Cary , NC ) .
The statistical tests were performed using the Statistical Package for Social Sciences ( SPSS ) for Windows ( Version 13.0 , Chicago , IL , USA ) .
De novo assemblies were created for each isolate , using Roche Newbler package ( v. 2.6 ) , CLC Genomic Workbench 6.5.1 , and SMRT analysis 2.0.1 , for isolates sequenced by 454 , Miseq ™ , and PacBio , respectively .
All draft genomes were annotated using NCBI ’ s Prokaryotic Genomes Automatic Annotation Pipeline ( PGAAP [40] , ) .
The raw reads of each sample were mapped to the closed reference genome , CFSAN 001339 , using Novoalign V 2.08.02 ( http://www.novocraft.com ) , and the variants were called using SAMtools and stored in a VCF file [43] .
Data were analyzed using FlowJo software 10 ( Tree Star , USA ) .
Samples were analyzed using a FACS Canto flow cytometer ( Becton Dickinson ) , and data were analyzed using FlowJo software version 10 ( Tree Star , USA ) .
Statistical analyses were performed with Graphpad Prism 5.0 ( GraphPad Software Inc . USA ) using two tailed Student ’ s t test with Welch ’ s correction .
Data analyses were performed using R software ( R Development Core Team , 2010 , version 2.11.1 ) .
The meteorological variables were used as input for the Fire Weather Indices Calculator software , developed in the frame of the ALPFFIRS project by WSL ( www.wsl.ch ) , in order to calculate fire weather indices for each day of the time interval considered ( Table 1 ) .
All model analyses were performed with the R statistical package , version 3.0.2 [48] .
For the Maxent model , we used the ‘ dismo ’ R package ( version 0.8 - 17 ) with the Maxent default settings .
All statistical tests were run using the R statistical packages version 3.0.2 [48] .
Image acquisitions were performed by an observer blind to the treatment groups using a CCD camera ( Model CFW - 1612C , Scion Corporation , MD , USA ) attached to an Olympus microscope and connected to a MacIntosh computer ( Software : ImageJ , Wayne Rasband , NIH , Bethesda , MD , USA ) .
All statistical analyzes were performed with GraphPad Prism 5.0 for MacOS X ( GraphPad Software Inc , La Jolla CA ) and all data are expressed as mean ± SEM .
Standardized regression coefficients ( SCR ) were calculated using the sensitivity package of the R - project [50] .
Statistical analysis was conducted with the Statistical Package for the Social Sciences ( SPSS Inc . Chicago , Illi - nois , USA ) version 21.0 .
This analysis focuses on the 181,764 beneficiaries who were consistently eligible for benefits over at least 22 months in 2009 and 2010 , who also received DCG codes . ( Sightlines DxCG Risk Solutions V 3.0 , Verisk Health Inc ) Beneficiary age and gender were available .
The pore structure homology model of the zebrafish Kir 7.1 channel ( residues 40 to 178 ) was created from the template KirBac 1.1 structure using DS modeling software version 1.1 ( Accelrys , http://www.accelrys.com ) .
The channel current was recorded using a patch - clamp amplifier ( Axon 200B ; Axon Instruments , http://www.axon.com ) , low - pass - filtered at 1 kHz ( − 3 dB ) by an eight - pole Bessel filter , digitized by an AD converter ( Digidata ; Axon Instruments ) , and continuously acquired on a computer ( Dell ) with commercially available software ( pCLAMP 9 ; Axon Instruments ) .
Calculation of sample size per species and sampling area was based on estimated population sizes derived from the regional hunting bags , and performed using WinEpiscope ™ 2.0 software [39] , with the aim of detecting infection and assuming a prevalence of 5 % in each species with 95 % confidence level .
Statistical analysis , including the calculation of 95 % - confidence intervals for bTB and MTBC prevalence , was performed using NCSS 2007 statistical software ( Version 07.1.15 ; Kaysville , UT , USA ) .
fMRI data were analyzed using SPM 8 ( Wellcome Trust Centre for Neuroimaging , http://www.fil.ion.ucl.ac.uk/spm ) .
The anatomical borders for each area of interest were defined by using overlays generated by the Wake Forest University ( WFU ) Pickatlas [31] toolbox for SPM .
Data analysis and visualization were performed using Excel and “ R ” , version 3.1.3 .
Analyses were performed using SPSS 18.0 ( SPSS Inc . , Chicago , IL , United States ) .
Stimuli were controlled by a computer running Matlab ( Mathworks ) with Psychtoolbox [73] and Eyelink Toolbox [74] .
The Markov model was built in Excel ; statistical analysis to parameterize the model was undertaken in STATA version 11 .
SPSS 22.0 for Windows ( SPSS Inc . , Chicago , IL ) was used for the analyses .
Data analysis was performed with EpiInfo 3.5.4 and Stata 10 software .
Interrater reliability ( kappa ) was calculated with SPSS version 15.0 ( SPSS Inc , Chicago , Illinois ) , and chi - square analysis of categorical data was performed with JMP version 5.1 ( SAS Institute , Cary , North Carolina ) .
Actigraphs were initialised for each child using an Actigraph Reader Interface Unit ( RIU - 41A ) with RIU software ( version 2.26B , MTI Health Services , http://www.mtifwb.com ) .
All analyses were performed using Stata version 8 ( StataCorp , http://www.stata.com ) .
Preliminary quality control of raw reads was carried out with FastQC software v 0.11.2 [89] .
Expression Analysis of mRNAs and miRNAs : Statistical analyses to compare mRNA and miRNA expression profiles were performed using the " R " statistical environment edgeR [96] , vegan [97] and gplots [98] packages .
The Pearson correlation coefficient between the two analyses was calculated using IBM Statistical Package for Social Sciences software ( SPSS , ver. 21 ; IMB SPSS Inc . , Chicago , IL , USA ) and differences were considered as statistically significant if the p - Value was < 0.05 .
Functional Analysis of gene expression data : The RNA - Seq differentially expressed ( DE ) gene lists obtained for each comparison ( PP vs NN , NP vs NN , PP vs NP ) were submitted to the Qiagen Ingenuity Pathway Analysis ( IPA ; Ingenuity Systems Inc . , USA ) .
Predicted targets of known miRNAs were then analyzed with the TargetScan software v 7.0 [102] .
Statistical analyses were performed using STATISTICA Windows XP version 12 .
All analyses were performed with PASW ™ for Windows ™ version 18.0 software ( formerly SPSS Statistics Inc . Chicago , Illinois ) and survey procedure for complex sampling design .
Statistical significance was set at p ≤ 0.05 , and analysis was performed using SAS software program ( version 9.1 ; SAS Institute Inc . , Cary , NC ) .
SPSS version 15.0 software ( SPSS Inc . 2007 , Chicago , Illinois , USA ) was used for statistical calculations .
SAS version 9.2 ( SAS Institute , Inc . , Cary , NC , USA ) was used for all the analyses .
fMRI data were analyzed with the BrainVoyager 2.1 software package and in - house scripts drawing on the BVQX toolbox in MATLAB .
Statistical analysis of the results was performed with the use of Statistica 10.0 for Windows by StatSoft .
Data were analyzed with the Statistical Package for the Social Sciences ( SPSS ) for Windows ( Version 19.0 ) .
Using ArcGIS ( version 10.0 , Environmental Systems Research Institute , Redlands , California ) , we created a uniform pattern of sample points with a distance of 4 km apart for both study areas .
We carried out imputation to HapMap release 22 using Mach 1.0 , Markov Chain Haplotyping [16] .
We carried out imputation to HapMap release 22 ( after excluding SNPs with MAF < 1 % , SNP call rate < 98 % and HWE p value < 1 × 10 − 6 ) using Mach 1.0 , Markov Chain Haplotyping [16] .
We carried out genome - wide association analyses for BMDC using additive linear regression in Mach2QTL for both ALSPAC and GOOD ( using GRIMP [20] for the GOOD analyses ) .
Additive linear regression analyses were carried out for the associations between these SNPs and BMDC in PLINK [21] ( ALSPAC ) or in SPSS Statistics 17.0 ( MrOS Sweden ) using age , sex , height and weight ( ln ) as covariates .
We carried out association analyses using additive linear regression in PLINK for ALSPAC and in SPSS Statistics 17.0 for GOOD and MrOS Sweden .
Sequence raw data was analysed with Sequence Scanner v 1.0 ( Applied BioSystems ) program and sequences were subsequently aligned with BioEdit software version 7.0.0 [30] in relation to the revised Cambridge Reference Sequence [31] .
For each population , the number of different haplotypes ( K ) , the number of polymorphic sites ( S ) [58] , the gene diversity ( H ) [59] and the nucleotide diversity ( π ) [58] , [59] were estimated using the software Arlequin ver. 3.11 [60] .
Multidimensional scaling . ( MDS ) was used to represent genetic distances in a two - dimensional space using SPSS ver. 17.0 ( SPSS Inc . ) .
Phylogenetic networks [62] among haplotypes were constructed using the program Network 4.610 ( www.fluxus-engineering.com ) .
Spatial frequency distribution maps of East Eurasian lineages in Pre - Iron Age and Iron Age periods were obtained using Surfer version 8.05 ( Golden Software ) .
QTL analysis was performed using QTL Express ( http://qtlcap.ed.ac.uk ) , qxpak v 2.16 [55] and R / Qtl [56] for the standard interval mapping and epistatic analyses .
The survey data were entered into an Access database using a two - pass data verification process and analyzed using SPSS v 15.0 software .
The reaction network consists of 173 chemical species and 6,581 unidirectional reactions . ( The size of the reaction network reflects the number of protein phosphoforms and protein complexes that can arise from the interactions represented by the rules of the model . ) BioNetGen ’ s built - in ODE solver , CVODE from the SUNDIALS package [69] , was then used to numerically integrate the ODEs , using default settings .
The steps described above were performed automatically by BioNetGen and invoked using point - and - click commands available within RuleBender [70] , which provides a graphical user interface for accessing BioNetGen ’ s capabilities .
Statistical analyses were performed using SAS software , version 9.4 ( SAS Institute , Cary , North Carolina ) .
Fiber tracts between the amygdala and each of the other four ROIs were reconstructed using the probabilistic method as implemented in the FDT tool of the FSL software ( http://fsl.fmrib.ox.ac.uk/ ) ( For details , refer to S1 Text ) .
All statistical analysis was performed using the Stata / SE software ( release 13.1 ) ( Stata Corp LP , College Station , TX , USA ) , and the statistical significance level was set at P = 0.05 in all statistical inferences .
All data analyses were carried out in R version 3.3.0 using packages ‘ Mice ’ , ‘ lattice ’ , ‘ Survival ’ , mitml ’ , and ‘ survC 1 ’ .
The analysis was conducted in Mplus 6.0 for Windows [43] .
SPM 8 ( http://www.fil.ion.ucl.ac.uk/spm ) was used for analysis .
The simulation of the pedigree and recalculation of LRS data was implemented with a purpose - specific programme coded in MATLAB ( MathWorks ) , with animal model analyses implemented in AsReml ( VSN International ) as described above .
Statistical analyses were performed using Stata 13 ( StataCorp , College Station , TX ) .
In this study we used the Skeeter Buster model [16] , a stochastic , biologically detailed , spatially - explicit model of Ae . aegypti populations , based on biological elements of the CIMSiM model [49] .
All analyses were done using Stata version 9.2 and ESRI ArcGIS version 9.2 .
Sperm concentration and motility were assayed using a computer - aided sperm analyses ( CASA ) system coupled to a phase contrast microscope ( Nikon Eclipse model 50i ; Nikon Instruments Europe B.V . , Izasa S.A . ; negative contrast ) and employing Sperm Class Analyzer ( SCA , Barcelona , Spain ) v. 4.0 . software ( Microptic S.L . , Barcelona , Spain ) [35] .
All statistical calculations were made using TIBCO Statistica software v. 13.3 ( TIBCO Software Inc . ) .
All the analyses were performed using the Stata 13 statistical program ( Stata Corporation , College Station , TX , USA ) .
Based on these 946 SNP positions we then computed a Maximum Parsimony ( MP ) tree using MEGA 5 with 200 bootstrap replicates [4] .
All statistical analyses were performed using SAS 9.3 ( SAS , Cary , NC , USA ) , with the significance level set to 0.05 , two - tailed .
Our pharmacokinetic modeling and simulation were performed by use of ADAPT II program [44] and a MATLAB program developed in our own lab for numerical solution of differential equations defined in Eqs . ( 1 ) and ( 2 ) [45] , [46] , [47] .
Doppler scans were replayed back on the quantification software ( Q - LAB v 6 , Philips Healthcare , Andover , MA , USA ) and three images per ovary with the greatest area of blood flow were chosen for quantification by two observers blinded to the treatment groups .
Primer 3 Input version 0.4 , online software , was used to design forward and reverse primers ( Table 2 ) from DNA sequences obtained from Ensembl Genome Browser , sequences were checked for specificity using Basic Local Alignment Search Tool and validity confirmed as previously described [26] .
For the analysis , we used the SPSS software for Windows , version 15.0 ( SPSS Ltd . ) .
Behavior data was analyzed using HVS Image 2015 software ( HVS Image ) .
Further , protein - coding nucleotide sequences were translated to amino acids using MEGA 4.1 [41] to check for premature stop codons .
Alignments were first conducted using Clustal W [43] integrated into MEGA v. 4.1 [41] while employing default parameters .
Identical haplotypes were collapsed using DnaSP , v. 5.0 [44] .
The search was conducted using PAUP * v. 4.0b 10 [45] with 100 random stepwise additions and TBR branch swapping .
For the first dataset , associations among the 214 D - loop haplotypes were also visualized by a full median - joining network [46] , [47] with MP post - processing [48] as implemented in Network v. 4.5 ( www.fluxus-engineering.com/sharenet.htm ) .
For the second dataset , phylogenetic relationships were also inferred using Bayesian inference as implemented in MrBayes v. 3.1.2 [49] .
The best - fitting nucleotide substitution model for each gene ( 16S : GTR + I + G , Cytb : GTR + G , D - loop : HKY + I + G ) was selected based on the Akaike Information Criterion as implemented in Modeltest v. 3.7 [50] using default parameters .
The pairwise genetic differentiation values were assumed to measure the extent of DNA divergence between populations , and the significance was tested using 1,000 permutations with Arlequin v. 3.11 [51] .
Correlation of geographic and genetic distances was determined using Mantel ’ s permutation test with 10,000 permutations executed by IBDWS v. 3.15 [52] .
Divergence times were estimated using a Bayesian MCMC method implemented in beast v. 1.5.3 [57] , which employed a relaxed molecular clock approach [58] .
The dataset was partitioned and each optimal nucleotide substitution model was selected by using the Akaike Information Criterion as implemented in Modeltest v. 3.7 [50] .
The adequacy of using a 50 % burn - in to generate MCMC trees and for convergence of all parameters was assessed visually using Tracer v. 1.4.1 [59] .
Subsequently , the sampling distributions of two independent replicates were combined using the software LogCombiner v. 1.5.2 [54] , and the resulting 100,002 samples were summarized and visualized using TreeAnnotator v. 1.5.2 [54] and Fig Tree v. 1.2 [60] .
All loci were collected as an EXCEL file , and then converted into the computable files using convert [61] .
Tests for linkage disequilibrium were checked by using the GenePop v. 4.0 [62] .
The total number of alleles ( NA ) , allelic richness ( R ) , gene diversity ( GD ) and allele frequencies were calculated in Fstat v. 2.9.3.2 [63] .
The presence of genetic bottlenecks was tested by using the heterozygosity excess method [64] implemented in Bottleneck v. 1.2.02 [65] .
First , we assessed population structure by using pairwise FST values calculated in Arlequin v. 3.11 and the Bayesian clustering approach implemented in Structure v. 2.3.3 [66] , [67] , [68] .
Because spatially explicit Bayesian clustering methods can be powerful when inferring genetic structure [69] , [70] , particularly at low levels of differentiation [71] , [72] , we used Geneland v. 4.0.3 [72] , [73] , [74] to search for structure in the rhesus macaque .
We also used the maximum likelihood and Bayesian inference [75] , [76] , [77] algorithms in migrate v. 3.3.2 [78] to estimate test the null hypothesis of unbiased , equal rates of migration rates and equal effective population sizes between the two largest haplogroups resolved in the haplotype network .
The raw data from the analysis were analyzed using Coffalyser.NET ( beta version , MRC - Holland , Amsterdam , the Netherlands ) .
Basic preprocessing was performed using SPM 12 ( www.fil.ion.ucl.ac.uk/spm ) .
All further preprocessing steps were carried out using Nilearn 0.2.5 [30] in Python 2.7 .
The groups were allowed to analyze the training and test data in any way they deemed fit , but all used a combination of the following methods : ( i ) Visual inspection with dynamic varying of thresholds using a software such as Mricron or FSLView . ( ii ) Voxel - wise correlation of brain maps from the training and the test set , to find the blocks which are most similar to each other . ( iii ) Voxel - wise correlations of brain maps with maps from NeuroSynth [33] , to find the keywords from the NeuroSynth database whose posterior probability maps are most similar to the participant ’ s activity patterns .
The selected maps were then clustered using K - Means , as implemented in Scikit - learn 0.17 [34] .
All data processing and statistical analyses were performed with the Statistical Package for Social Science ( SPSS ) software , vers . 18.0 ( SPSS , Chicago , IL , USA ) and SAS vers . 8.2 ( SAS System for Windows , SAS Institute , Cary , NC , USA ) .
The total number of licks , cluster number , cluster duration ( s ) and number of licks per cluster were calculated for each 1 - h session using a custom written MATLAB script ( R 2010a , The MathWorks ™ ) .
The statistical tests were performed using GraphPad ( GraphPad Software Inc . , La Jolla CA , USA ) , MATLAB ( R 2010a , The MathWorks ™ , Natick , MA ) and NeuroExplorer ( Nex Technologies , AL , USA ) .
Reads were mapped to the Genome Reference Consortium GRCm 38 mouse assembly using Tophat 2 ( v 2.0.8 ) [17] with the Illumina iGenomes package ( mm 10 ; http://support.illumina.com/sequencing/sequencing_software/igenome.html ) .
Reads were combined into transcripts and differential expression was tested using Cufflinks ( v 2.1.1 ) [18] .
The hypergeometric test was implemented in the Database for Annotation , Visualization and Integrated Discovery ( DAVID , http://david.abcc.ncifcrf.gov ) [23,24] .
Gene Ontology ( GO ) results were reported using the DAVID Functional Annotation Tool ( FAT ) classes to facilitate interpretation .
Networks were visualized using the BisoGenet plug - in [27,28,32] within the Cytoscape environment [24,33] .
The same epochs of electroencephalographic activity used in the sLORETA analyses were also imported into MapWin software [23] for the computation of microstates and their related parameters ( i.e. duration of microstate , occurrence of microstate class , etc . ) .
UKBB samples were genotyped on the UK Biobank Axiom array at the Affymetrix Research Services Laboratory in Santa Clara , California , USA and imputed to the Haplotype Reference Consortium ( HRC ) panel [54] .
We performed SNP QC using PLINK v 1.07 [58] .
SMARTPCA v 10210 [59] was used for principal component analysis ( PCA ) .
Imputation and genome wide association analyses : SCOOP , STILTS and UKHLS single - variant association analysis : Genotypes from SCOOP , STILTS and UKHLS controls were phased together with SHAPEITv 2 [61] , and subsequently imputed with IMPUTE 2 [62,63] to the merged UK 10K and 1000G Phase 3 reference panel [64] , containing ~ 91.3 million autosomal and chromosome X sites , from 6,285 samples .
Analyses of 1,456 SCOOP , 1,471 STILTS and 6,460 controls ( BMI range 19 - 30 ) of European ancestry were based on the frequentist association test , using the EM algorithm , as implemented in SNPTEST v 2.5 [65] , under an additive model and adjusting for six PCs and sex as covariates .
Variance explained was calculated using the rms package [71] v 4.5.0 in R [72] and Nagelkerke ’ s R 2 is reported .
The R package GTX ( https://cran.r-project.org/web/packages/gtx/index.html ) was used to transpose genotype probabilities into dosages , and a combined dosage score , weighted by the effect size from GIANT , for 97 BMI SNPs [24] was calculated and standardised .
Statistical analysis was performed using JMP ( JMP 7.0 , SAS Institute Inc . , NC , USA ) .
Statistical analysis was performed employing the commercial software packages SAS 9.3 ( SAS Institute Inc . , Cary , North Carolina , USA ) and Statistical Package for the Social Sciences , Version 19.0 ( SPSS Inc . , Chicago , IL , USA ) .
The STATA software ( Version 11.0 ; Stata Corp , College Station , TX , USA ) was used for the statistical analyses .
All analyses were done with the SPSS 19.0 software ( SPSS Inc . , Chicago , IL ) .
Models were fitted using the R package bnlearn [32] .
To control for possible confounding effects , age and gender were used as independent variables in a multiple logistic regression analysis for adjustment by commercially available software ( Statistical Package for Social Sciences , version 16.0 for windows , SPSS Inc . , Chicago , IL , USA ) .
Haplotype frequencies were estimated using GENECOUNTING v 2.2 , which computes maximum - likelihood estimates of haplotype frequencies from unknown phase data using an expectation - maximization algorithm [43] .
Furthermore , we performed power calculations for case - control genetic association analyses using PGA v 2.0 [45] .
Maps were created in ArcGIS 9.3 ( ESRI , Inc . ) and Photofiltre 6.5.1 .
Statistical analysis and figures were completed in R version 2.15.3 [10] .
We used EstimateS v 8.2.0 [11] to generate a presence - absence accumulation function of subtypes and calculated the nonparametric estimate of subtype richness with 95 % confidence intervals using the Chao 2 estimate and 50 randomizations with replacement [6] .
All radio - frequency signals were processed off - line using a custom - developed program of Matlab ( Version R 2008 , MathWorks , Inc . , MA , USA ) .
We conducted all the data analyses using R ( Version 3.1.2 , The R Foundation for Statistical Computing ) .
All analyses were performed using “ Statview 4.5 ” statistic software ( SAS Institute Inc . , Cary , USA ) .
The data analysis was done using Stata version 11 ( College Station , TX : StataCorp LP . ) .
Changes in other biological parameters were examined using one - way ANOVA with PASW Statistics ver. 17 ( SPSS , Inc . , Chicago , IL , USA ) .
B . ( trial statistician ) using Stata / SE 13.1 .
The within - trial economic analysis ( conducted by T . H . S . using Stata / SE 14.1 ) compared the costs and QALYs in the standard care and intervention groups from the perspective of the NHS .
Data were analyzed with BrainVoyager QX ( Brain Innovation ) software .
All recordings were acquired using Scan 4.3 ( Compumedics Neuroscan ) and stored for off - line treatment .
Eye blinks were identified by a threshold criterion of ± 100 μ V , and their contribution was removed from each dataset using principal component analysis by singular value decomposition and spatial filter transform using Scan 4.3 ( Compumedics Neuroscan ) .
The EEG signal processing was implemented in MATLAB using in - house scripts ( LAN toolbox , available online at http://lantoolbox.wikispaces.com/ , e.g. [26] ) .
For the source estimation and head model , we used the BrainStorm [27] and openMEEG toolboxes [28] .
An a - priori sensitivity power analysis ( G * Power 3 software ; [21] revealed that our final sample size ( four equal - size groups of 11 participants ) is large enough to detect a within - between interaction corresponding to an effect size as small as η p2 = .1 with a statistical power of ( 1 - β ) = .95 ( given α = .05 ) .
SMI software ( Experiment Center ™ and iView X ™ ) were used to collect and record calibration , present the stimuli , and record gaze data .
Data pre - processing : Sequencing adapters were removed from the FASTQ files with cutadapt [24] and sickle [25] .
Sample QC : Samples were excluded from the analysis based on the following criteria : 1 ) Samples with a mean depth < 30x or < 70 % of exon targets covered at < 20x were excluded from further analysis ; 2 ) samples with > 3 standard deviations from mean in number of alternate alleles , number of heterozygotes , transition / transversion ratio , number of singletons and call rate as calculated with the PLINK / SEQ i - stats tool ( https://atgu.mgh.harvard.edu/plinkseq/ ) ; 3 ) call rate < 97 % ; 4 ) ethnically unmatched samples as identified by multi - dimensional scaling analysis with PLINK version 1.9 [29] ; 5 ) PI _ HAT score > 0.25 as calculated by PLINK version 1.9 to exclude related individuals .
Variant annotation : Variants were annotated with ANNOVAR [31] version 2015 , Mar 22 using RefSeq and Ensembl versions 20150322 and the dbNSFP [32] version 2.6 annotations including nine scores for missense mutations ( SIFT , PolyPhen 2 HDIV , PolyPhen 2 HVAR , LRT , MutationTaster , MutationAssessor , FATHMM , MetaSVM , MetaLR ) , the CADD score , and three conservation - based scores from GERP + + , PhyloP and SiPhy .
CNV calls were annotated using bedtools version 2.5 [36] .
Burden analysis of large and rare deletions : Excess deletion rate of the large deletions ( length > 400 kb ) in subjects with epilepsy compared to the controls was measured as described in [13] using PLINK version 1.9 [29] .
Genes that were expressed in brain [42] and located within deletion boundaries were used as input for an enrichment analysis using the Ingenuity Pathway Analyser ( IPA ™ ) [43] .
The R GeneOverlap package ( https://bioconductor.org/packages/release/bioc/html/GeneOverlap.html ) was used to compute the p - value .
For all community multivariate analyses , PCORD ( version 4.25 ) was used [19] .
We checked returned sequences using the RDP Classifier v 2.2 [25] , and discarded a single sequence from the Snodgrassella set not matching Betaproteobacteria .
The remaining sequences were curated using Geneious , version 5.5 [26] .
WHO 2006 growth standards were used to calculate WHZ and HAZ using the ZSCORE 06 Stata command [51] .
All statistical analyses were conducted using Stata 12.0 ( Statacorp , College Station , TX ) .
NMDS plots were constructed using R with the Vegan Package [25] .
All core areas were calculated using the R software platform ( v. 3.1.2 [103] ) and the adaptive mode version of T - LoCoH [101] .
We ran permutation tests on the compiled version of SOCPROG 2.5 for each seasonal dataset , taking the coefficient of variation of the association index as our test statistic [73,109] .
A distribution of averages was then used to derive 95 % confidence intervals using the first - order normal approximation as implemented in the boot package for R [114] .
Randomization Software EASY RA 1 Easy Randomizer Version 4.1 , State University of Michigan , USA was used and Njiru was randomly designated as the intervention division and Makadara as the control area .
Data analyses were conducted , using SAS software ( version 9.2 , SAS Institute , Cary , NC , USA ) by JM ( biostatistician at Radboud University Nijmegen Medical Centre ) .
The IBM SPSS Statistics version 24 was utilized for the statistical analysis .
Data were analysed using IBM SPSS Statistics 21 and IBM SPSS Amos 21 for Windows ( IBM Corp . , Armonk , NY ) .
All statistical analyses were conducted using Stata 12.1 ( StataCorp LP , College Station , Texas , USA ) .
Two separate multiple regression models were used to evaluate the relationships between TL in 2013 and 1 ) “ change in number of surviving offspring ( 2000 - 2013 ) ” , maternal age at first birth and average inter - birth interval , as well as 2 ) “ total number of surviving offspring ” , maternal age at first birth and average inter - birth interval using JMP ( version 12 ; SAS Institute ) .
The visual input was presented using the MATLAB - based Psychophysics Toolbox [15,16] , and they were delivered to the subjects through a binocular goggle system ( NordicNeuroLab , Norway ) mounted on the head coil .
MRI and fMRI data were preprocessed by using FSL [17] and AFNI [18] .
Instead , we used a non - parametric resampling based statistical inference as implemented in ISC - toolbox ( www.nitrc.org/projects/isc-toolbox/ ) and described in details elsewhere [20] .
All analyses were conducted using STATA 11.0 ( StataCorp , College Station TX , USA ) .
Choroidal segmentation and thickness analyses were performed automatically with custom MATLAB ( MATLAB 2017b , The MathWorks , Inc . , Natick , MA , USA ) software for choroid segmentation [21] .
Vitreous chamber depth was calculated in Excel ( Microsoft Excel 2013 , Microsoft Corporation , Redmond , WA , USA ) by subtracting the corneal thickness , anterior chamber depth and lens thickness from the axial length .
All analyses were performed using SAS SURVEY procedures available in SAS version 9.04 software .
The ReMIT project is built around the dcm4che collection of open source applications , in particular its DICOM Image Manager / Image Archive server , dcm4chee .
The software is written as a native plugin in Objective - C and is integrated within the mixed C / C + + / Objective - C environs of OsiriX .
The presentation of pictures was synchronized with the monitor ' s refresh rate and presented with the software Presentation ( Neurobehavioural systems , www.neurobs.com ) .
Spatial preprocessing and statistical analysis of functional images were performed using SPM 8 ( Welcome Department of Cognitive Neurology ) .
Functional MRI data were pre - processed and analyzed using Statistical Parametric Mapping SPM 8 ( Wellcome Department of Cognitive Neurology , London ) software implemented in MATLAB 7.8 ( Mathworks Inc . , Sherbom , MA ) .
This peak value was selected , unless identified outside of the brain structure of interest upon visual inspection of the individual normalized anatomical T1 image and verification of localization in SPM toolbox Anatomy atlas [51] , in which case the maximum value that fitted the anatomical location was selected .
To quantify the evidence in support of the null hypothesis in these two comparisons , we computed the corresponding Bayes factors ( using JASP 0.7.5.6 ; www.jasp-stats.org ) .
The Species Distribution Modeling ( hereafter SDM ) for jaguar occurrence in Caatinga biome was generated by the maximum entropy algorithm , as implemented in Maxent software 3.3.3e [31] [32] .
Following the procedures proposed by Rabinowitz and Zeller [19] , we used the Cost - Distance function ( Spatial Analyst , ArcGis 9.3 ) to delineate movement cost grids for each PJCU .
We used the LiDAR Analyst 5.0 extension [50] of ArcGIS 10.1 [51] to identify biophysical attributes of trees in the study area that are relevant to the estimation of biomass .
To study modularity we used ‘ netcarto ’ [5] and Pajek [42] .
We used ‘ R - bipartite ’ [48] to quantitatively assess interacting and distributional patterns between trophic levels of each sub - network and the set of tree hollows assessed .
Small - for - gestational age was defined as an infant being below the 10th weight centile for gestational age as determined by the INTERGROWTH - 21st Newborn Size Application Tool using standards derived from births in eight ethnically distinct countries ( http://intergrowth21.ndog.ox.ac.uk/ ) .
The interval confidence of apparent prevalences were calculated with the “ EpiR ” package , the graphics were performed with the “ ggplot 2 ” package and the GAMs were implemented in the “ mgcv ” statistical package , all from the R statistical software [43] .
The spatial data representation and mapping was made with the software QGIS 2.14 Essen [44] .
Individual - level covariates are based on administrative records , ICD - 9 diagnosis and procedure codes , and Clinical Classifications Software ( CCS ) codes , developed by HCUP for use with ICD - 9 codes .
Covariates include maternal age , race / ethnicity , and insurance status ( primary payer : private insurance , Medicare , Medicaid , self - pay / uninsured , or other ) , and maternal and infant medical conditions , including diagnoses of the following complications of pregnancy , labor , and delivery : diabetes in pregnancy ( both diabetes mellitus and gestational diabetes ; ICD - 9 codes 6488XX , 250XX ) , hypertension in pregnancy ( including pre - eclampsia and eclampsia ; ICD - 9 codes 6420X , 6421X , 6422X , 6423X , 6424X , 6425X , 6426X , 6424 , 6425 , 6426 , 6426XX ) , hemorrhage during pregnancy or placental complications ( including placenta previa and placenta accreta ; CCS code 182 ) , fetal disproportion or obstruction of labor ( CCS code 188 ) , and fetal distress ( CCS code 190 ) .
We used Markov chain Monte Carlo methods to fit Bayesian analytic models , where distributions for the model parameters were first estimated with predictive quasi - likelihood approximation with a second - order Taylor linearization procedure as implemented in MLwiN version 2.1 [35] .
The following variables were examined using Poisson regression with robust variance estimation to account for clustering of cats within shelters ( Stata 13.1 / IC , StataCorp LP , College Station , Texas ) for possible associations with monthly URI rates between shelters : double compartment housing ( no / yes ) , intake housing floor space ( 3 - 6 ft 2 , 6 - 8 ft 2 , > 8 - 10ft 2 { .28 - .56m 2 , .56 - .74m 2 , > .74 - .93m 2 } ) , hiding space provided in intake housing ( no , sometimes , always ) , mixed - age housing ( no , yes ) , frequency of cat moves in and out of the cage in the first week ( ≤ 2 moves , > 2 moves ) , use of intranasal vaccine ( no , yes ) and monthly shelter intake ( natural log transformation ) .
Meta - analyses were carried out using Comprehensive Meta - Analysis ( V 2.0 , Biostat , Englewood , NJ , USA ) .
Our analysis is an alternative to a another approach , which has been implemented by Caldara and colleagues in a free Matlab toolbox called iMap [42] .
The AFNI ( http://afni.nimh.nih.gov ) function 3dFDR was applied to each of the statistical maps .
Statistical analyses were performed with the SAS software package , version 9.2 ( SAS Institute , Cary , NC , USA ) , and Stata / SE software , Version 12.1 ( StataCorp , College Station , TX , USA ) .
Absolute differences and relative risks were estimated with the GENMOD procedure in SAS version 9 ∙ 3 ( SAS Institute , Cary , N.C . ) The absolute and relative effect of the CCP was estimated for each of the four baseline treatment status groups .
All analyses were carried out using Stata version 11 ( Stata Corp . LP , College Station , TX , United States of America ) .
Potential trade - offs were identified using radar plots in R ( version 3.2.2 [30] ) and the fmsb package [31] .
The vocalization synthesis relied on the articulatory synthesizer developed by Boersma and available in Praat [ 61 , 66 ] .
All analyses were performed with Stata statistical software , version 11.2 ( StataCorp , College Station , TX ) .
Significant differences were determined using the Mann - Whitney non - parametric two - tailed test using GraphPad Prism Version 5 .
All of this analysis was implemented using Matlab , and the code is available for download from a public GitHub repository https://github.com/EmoryUniversityTheoreticalBiophysics/C.-elegans .
In silico Analysis of sc - srp - 6 : The sc - srp - 6 full - length cDNA was used in a BLAST search query ( http://ncbi.nlm.nih.gov/blast ) , and sequence alignments were created with the ClustalW program ( http://www.ebi.ac.uk/clustalw ) .
Protein motifs were predicted using SMART ( http://smart.emblheidelberg.de ) , and SignalP 3.0 was used to identify the signal peptide ( http://www.cbs.dtu.dk/services/SignalP ) .
Statistical analysis was performed using a one - way ANOVA followed by Bonferroni multiple comparison tests ( Statistical Package for the Social Sciences software , SPSS version 13.0 ) .
Several softwares and R packages are available for Rasch model analysis such as ConQuest ( https://shop.acer.edu.au/group/CON3 ) , RUMM ( www.rummlab.com.au ) , ltm ( cran.r-project.org/package=ltm ) and eRM ( cran.r-project.org/package=eRm ) .
Protein - protein interaction data and functional findings were extracted from QIAGEN ’ s Ingenuity Pathway Analysis ( IPA , QIAGEN Redwood City , www.qiagen.com/ingenuity ) , manually analysed and supplemented by literature curation .
Analyses were conducted using Stata v 11 [16] .
The entire sequence of touches for each participant that contains the special runs was then entered into a Monte Carlo program ( TouchStat 3.0 ) [41] to determine if they were likely to have occurred by chance .
All paradigms were implemented and displayed using the Presentation ™ Software package ( Version 14.1 , http://neurobs.com ) .
All fMRI data were analyzed using the standard routines and templates from the software package SPM 8 ( v 4290 ; www.fil.ion.ucl.ac.uk/spm ) in MATLAB 7.7.0.471 ( R 2008b ) ( The MathWorks , Inc . ) .
The anatomical localization of activated brain regions was assessed both by the SPM anatomy toolbox [34] and the WFU - Pickatlas [35] .
We here applied the bootstrapping approach implemented in the SPM 8 LI - toolbox , which is the current gold standard [36] .
First , we quantified the reliability of the activation patterns by computing intra - class correlation coefficients ( ICCs ) for each voxel using the ICC toolbox extension within SPM [42] .
As a measure of the test - retest reliability of the degree of lateralization , we computed an ICC ( two - way mixed model with absolute agreement using SPSS ; IBM SPSS Statistics for Macintosh , version 22.0 ) for the LIs in the frontal and parietal ROI , respectively .
Statistical analyses were performed with IBM SPSS 23.0 Statistics for Windows ( SPSS Inc . , Chicago , IL , USA ) or GraphPad Software .
Computation of the Gower index was implemented using the ' Gower ' computer program version 1.1 ( www.pbarrett.net/software.html ) .
Full details of the exact procedure are contained in the Bootstrap software used to perform the procedure ( Bootstrap Version 1.0 , http://www.pbarrett.net/Bootstrap/Bootstrap.html ) .
All statistical calculations , except those pertaining to the Gower calculations , were made using SPSS 18 ( IBM Corp . , Somers , NY , USA ) .
Analyses were performed using the Statistical Analysis System ( SAS ) 8.2 software ( SAS Institute Inc . Cary , NC , USA ) .
Data analysis was conducted using SPSS version 14 for windows .
Images were imported into Adobe Photoshop 8.0.1 ( Adobe Systems ) .
Data were acquired and analyzed using a Digidata 1440A interface and pClamp 10 software ( Molecular Devices ) .
Electrophysiological data were analysed using pClamp 10 and Igor pro software ( WaveMetrics ) .
Measurement of cortical thickness and hippocampus volume : After sections were Nissl - stained , images were captured with a video camera 3CCD ( DXC - 9300 ; Sony ) coupled to an image analysis system ( Visilog 6.3 ; Noesis ) .
The granule cell area was traced using an image analysis system ( Visilog 6.3 ; Noesis ) .
Code for calculating partition similarity , obtaining taxonomic data , and running the search algorithm are available on GitHub at https://github.com/esander91/SignedGroupModel .
In order to determine a relationship between biological aspects and behavioral problems statistical analyses were done using IBM SPSS 20 ( IBM SPSS 20 , Chicago , USA ) .
Data Processing and Feedback Signal Extraction : Immediately after acquiring the data from the primary motor and visual cortex localizer runs , the images were pre - processed with SPM 8 functions ( Wellcome Trust Centre for Neuroimaging , Queen Square , London , UK ) , i.e. realigned to the first scan of the respective localizer run , and smoothed with an isotropic Gaussian kernel with 4 mm full - width - at - half - maximum ( FWHM ) .
For the statistical analysis of the BOLD signal changes , we specified general linear models ( GLM ) with regressors for the experimental conditions defined in SPM 8 ( Welcome Trust Centre for Neuroimaging , UK ) .
All computations were carried out on a standard PC in Matlab 7.10 ( The Mathworks , Natick , MA ) .
Gray matter volume ( GMV ) calculation : The GMV of each voxel was calculated using Statistical Parametric Mapping software ( SPM 8 ; http://www.fil.ion.ucl.ac.uk/spm/software/spm8/ ) .
Imaging data were analysed using BrainVoyager QX ( Brain Innovation , Maastricht , the Netherlands ) .
These procedures were performed using the SPSS 11.5 software package [40] .
SPSS statistics for windows ( version 17.0 , Chicago , USA ) was used for analysis .
Allele scoring was performed using Genescan Software version 3.0 ( Applied Biosystems ) or Peakscanner Software 1.0 ( Applied Biosystems ) .
Tests for departures from Hardy - Weinberg equilibrium were performed using the Hardy - Weinberg probability function with default Markov chain parameters in Option One of GENEPOP 3.1 software [12] .
Genetic diversity estimates , observed and expected heterozygosity ( HO and HE ) , allele diversity , and population structure analyses such as Principal Coordinates Analysis ( PCoA ) and population assignment cluster analysis were measured using GenAlEx 6.5 [15] .
Relatedness within populations was examined using three programs : MLRELATE [16] , COLONY [17] and COANCESTRY [18] .
For all color measurements , we used an Ocean Optics USB - 2000 spectrometer with an R - 400 reflectance probe and PX - 2 pulsed xenon light source , and Optics OOIBase 32 v 2.0.6.5 software ( Ocean Optics , Inc . , FL , USA , 2002 ) .
The ESA ( European Space Agency ) Globcover land cover dataset ( http://due.esrin.esa.int/globcover ) was used based on 22 land cover classes as per the UN - FAO Land Cover Classification System at 300 - m spatial resolution [21] .
Geostatistical and GIS procedures were written in R - language using specific R - packages , such as rgdal , raster and mgcv , available online on : http://cran.r-project.org/ ( packages link ) .
Such a normalization step is not implemented in GRAB [14] suggesting that GRAB might be sensitive to ascertainment bias and general population diversity .
Relationship Estimation from Ancient DNA ( READ ) was implemented in Python 2.7 [73] and GNU R [74] .
We used vcftools version 0.1.11 [75] to extract autosomal biallelic SNPs with a minor allele frequency of at least 10 % ( 1,156,468 SNPs in total - similar to the aDNA data set used for the empirical data analysis [35] ; see below ) and to convert the data to TPED / TFAM files .
Dates were calibrated using the INTCAL 09 calibration curve and the program Calib v 6 [47] .
An age - depth model was developed using the date of core collection as an upper constraint ( 2011 AD ) , the five radiocarbon dates , the lower - most 210Pb date ( 50 cm depth ) , and the Ambrosia rise ( 40 cm depth ) , using the clam package for R [53] .
Figure generated using clam for R [53] .
Cluster analysis was used to determine boundaries between diatom assemblage zones in the stratigraphy , with the number of significant zones evaluated by the broken stick model , using the rioja package in R [ 62 , 63 ] .
Diatom and pollen assemblages were plotted as stratigraphies using C2 [64] ; C2 was also used to ordinate the samples using Detrended Correspondence Analysis ( DCA ) .
Ages were re - modelled for the Upper Mallot Lake pollen record using the top of the core ( 1993 AD ) , the three radiocarbon dates included in the database record , and the Ambrosia rise ( 15 cm depth ) with the clam package for R [53] ; pollen assemblages were ordinated using DCA and axis scores were plotted .
This map was generated using ArcGIS 10.2.2 ( www.esri.com ) .
The cross - correlation method and the significance tests for coefficients are implemented using Python 2.7.5 ( https://www.python.org ) .
All figures were drawn using Python 2.7.5 and Matplotlib 1.5.0 ( https://matplotlib.org/ ) .
We used statistical software R version 3.4.0 [21] to plot measurements , calculate the third - order polynomial that best fits the data using polynomial regression with the R - function lm ( y ~ poly ( 3 ) ) , implement the LT concepts and perform the statistical testing .
R was used with the following packages : dplyr 0.5.0 [22] , psych 1.7.5 [23] , tidyr 0.6.3 [24] .
Endocast rendering and volume estimation : A virtual endocast of MLDG 1704 was generated from computed tomography ( CT ) data in Mimics ( Ver. 13.02 ) by : Segmenting out extraneous material and generating a mask for MLDG 1704 , Generating a cutting plane and converting this mask into a 3D object , Positioning the 3D object such that it closed the open region of the cranium , Generating a mask from the repositioned 3D of the cutting plane , Combining the mask of MLDG 1704 with that of the cutting plane , Using the ‘ cavity fill ’ tool to create a partial endocast from this combined mask , A 3D surface mesh was then generated from this mask of the endocast and imported into Strand 7 ( ver. 2.4 ) , andA solid mesh of the partial endocast was then created in Strand 7 and the volume taken from the model summary .
Preprocessing and statistical analysis were performed in SPM 8 ( www.fil.ion.ucl.ac.uk/spm/software/spm8 ) .
The DARTEL toolbox was used for preprocessing [30] , with default settings for EPI data as outlined in the SPM 8 manual ( www.fil.ion.ucl.ac.uk/spm/doc/spm8_manual.pdf ) .
The pre - defined regions were based on the Talairach Daemon labels atlas in the WFU pickatlas [32,33] .
The remaining statistical analyses were carried out using IBM SPSS Statistics 22.0 .
All analyses were performed using GraphPad Prism 5 ( GraphPad Software , Inc . , La Jolla , CA , USA ) .
All questionnaire data were double - entered using Epidata 3.1 ( The Epidata Association Odense , Denmark ) .
Statistical Analyses ( S1 Table ) were performed using SAS V 9.4 ( SAS Institute Inc , Cary , North Carolina , USA ) .
The analyzes were performed using custom - written Matlab ™ ( The MathWorks Inc . , Version R 2014a , Natwick , MA , USA ) codes .
To examine the effects of distal loading within inclines and differences of loading between inclines , a marginal model ( population - averaged model ) was performed using the Statistical Package for Social Sciences 11.0 ( SPSS Inc . , Chicago , Illinois , USA ) .
SRM transition design was performed by the Skyline software [18] ( www.brendanx-uw1.gs.washington.edu ) on the protein - specific tryptic peptide sequences .
SRM - based analysis of saliva samples were carried out on a 4000 QTRAP ( ABSciex ) mass spectrometer using a NanoSpray II MicroIon Source and controlled by the Analyst 1.4.2 software ( ABSciex ) .
The Skyline data are publicly available through the Panorama [20] web site : ( https://panoramaweb.org/labkey/project/University%20of%20Debrecen/OSCC%20saliva/begin.view? ) The primary data were transformed into appropriate format of MSstats R - package [21-23] by an in - house developed software .
For evaluation of test performances multivariate receiver operating characteristic ( ROC ) curve analyses [26] were constructed by the Epi R - package [27] , the accuracy and the 95 % confidence intervals were calculated .
We fitted the ERMM with the R package “ Mixer ” [24] , [39] - [41] .
The Fast Louvain and Spectral algorithms were carried out using the Matlab “ Brain Connectivity Toolbox ” ( http://www.brain-connectivity-toolbox.net/ , accessed 15th June 2013 ) [49] .
To calculate the ARI scores , we used the function “ adjustedRandIndex ” in R software [58] , [59] and , for the ICC and AIC , we use the R function “ lmer ” [60] that employs a Restricted Maximum Likelihood procedure [61] to obtain estimates of , and AIC .
Survey data was analyzed in SPSS version 23 ( IBM SPSS Statistics , Armonk , New York ) after importation from CSPRO version 6.1 ( United States Census Bureau , Washington DC ) where it was entered and cleaned .
Cleaned FGD data was coded into salient themes in Nvivo 10 ( QSR international , Melbourne ) and analyzed using the content analysis method .
All tests were performed using the JMP 5.0 Statistics software package ( SAS Institute Inc . , Cary , NC ) .
VBM analyses were performed using SPM 8 ( http://www.fil.ion.ucl.ac.uk/spm ) as previously described [24] .
This correction was conducted using the AlphaSim program embedded into the REST Software ( http://www.restfmri.net/forum/REST_V1.8 ) , which applied Monte Carlo simulation to calculate the probability of false positive detection by considering both the individual voxel probability threshold and cluster size [30] .
All analyses were performed using SPSS software ( version 17.0 , IBM , China ) for Windows 7.0 .
The analyses were performed using IBM SPSS Statistics version 22.0 .
Program Cervus 3.0 [ 49 , 50 ] was used to calculate the number of alleles , allele frequencies , null allele frequencies and exclusion probabilities for each locus , and the combined exclusion probability .
The likelihood - based , COLONY 2 program [51] was used to analyze genetic relationships between the attending males , feeding females and the offspring in the nests .
Models were fitted using Stan 2.3.0 [78] , a Hamiltonian Monte Carlo sampler , to draw samples from the joint posterior density of the parameters .
Model code was generated using a convenience package for Rstan known as map2stan [79] .
All statistical analyses were undertaken using R 3.1.0 ( http://www.r-project.org ) .
Google ’ s deep learning framework TensorFlow [40] was used to train , tune , and test the CNN .
All tests were performed using the software Statistica ™ ( StaSoft Inc . , Tulsa , USA ) , version 8.0 and graphs were drawn with the software GraphPad Prism ™ , version 5.0 .
Data were preprocessed in FSL ( v. 5 ; http://fsl.fmrib.ox.ac.uk/fsl ) , which involved motion correction , brain extraction , high - pass filtering ( 100 s ) , and spatial smoothing ( 6mm FWHM ) .
To accomplish this , we used the Artifact Rejection Toolbox ( ART ; http://www.nitrc.org/projects/artifact_detect/ ) to create confound regressors for motion parameters ( 3 translation and 3 rotation parameters ) , and additional confound regressors for specific image frames with outliers based on brain activation and head movement .
All functional connectivity analyses were performed in the CONN toolbox 14.p [46] , with SPM 8 ( Wellcome Department of Imaging Neuroscience , London , UK ; www.fil.ion.ucl.ac.uk/spm ) .
Functional connectivity was performed in the conn toolbox v. 14p [46] .
In this analysis , values were log - transformed to conform to assumptions of linearity , and linear mixed effects models ( NLME package version 3.1 - 118 in R ) were used to account for ACTH challenge ( I and II ) and individual identity as random factors , because two individuals were tested in both challenges ( F1 and M4 ) and because we had multiple samples per individual which were not evenly distributed among the three day time periods .
All statistical tests , carried out in R Studio Version 0.98.1102 and SPSS ( IBM SPSS Statistics for Macintosh , version 22.0 ) , were two - tailed and the statistical significance level was set at 0.05 .
Visual and auditory stimuli were presented using Psychophysics Toolbox version 3.0.10 [ 22 , 23 ] running on MATLAB 7.9 ( MathWorks Inc , MA , USA ) and a Macintosh laptop running OS - X 10.6.8 ( Apple Inc , CA , USA ) .
The fMRI data were analysed using SPM 8 ( Wellcome Department of Imaging Neuroscience , London ; www.fil.ion.ucl.ac.uk/spm ) [40] .
The Ensembl data - mining tool BioMart ( http://www.ensembl.org/index.html ) was then used to convert these mouse gene IDs to human gene IDs , which resulted in a final set of 778 human genes .
We performed GSA using MAGMA [26] ( http://ctg.cncr.nl/software/magma ) and summary statistics from various GWAS .
Seed - based Functional Connectivity Group Analysis : Data processing was carried out using FMRIB Software Library ( FSL ) , www.fmrib.ox.ac.uk , Oxford U.K . , FSL version 4.1 [25] , [26] .
Statistical analysis was performed with the Statistical Package for the Social Sciences ( SPSS , Chicago , IL , USA , version 21.0 ) and SAS 9.2 for Windows 9.2 TS Level 1M 0 ( SAS Institute Inc . Cary , NC , USA ) .
Statistical software SPSS version 21 ( IBM SPSS , Armonk , NY , USA ) was used for all analyses .
The SNP markers were checked for genotyping errors using the PLINK [66] and PEDSTATS [67] packages and SNPs with genotyping errors were removed from the analysis .
Files were formatted for MCMC linkage analysis and an ideal set of SNPs was chosen for a marker panel with the Pedigree - Based Analysis Pipeline ( PBAP ) [68] , targeting marker spacing of 0.5 centimorgan ( cM ) , minor allele frequency ( MAF ) > 0.2 , and LD between markers < 0.04 .
MCMC - based linkage analysis was conducted with the gl _ auto and gl _ lods programs of the MORGAN 3.2 package [70-72] .
First , genotypes from the exomes were entered into the Copy Number Inference from Exome Reads ( CoNIFER ) package [74] .
For CoNIFER - based CNV discovery , reads from each exome were split into up to two consecutive 36mers and mapped using the single - end mode of mrsFAST [75] , then aligned to the hg 19 reference genome .
Here , we calculated CNVs with two software packages , PennCNV [76] and cnvHap [77] .
In Family A only , IBD analysis was performed using the HCS genotypes and the BEAGLE software package , Version 3.3.2 [79] .
Exome Variant Annotation , Filtering , and Single - Variant Genotyping : Exome variants were annotated using ClinVar ( http://www.ncbi.nlm.nih.gov/clinvar ) and Seattle Seq 137 ( http://snp.gs.washington.edu/SeattleSeqAnnotation137/HelpHowToUse.jsp ) , Variant Effect Predictor , Release 76 [ 81 , 82 ] , and searched with GEMINI [83] .
Variants were further evaluated with respect to their functions ( e.g. , missense , coding - synonymous ) , using the in - house Genome Variation Server , and predicted functional effects ( e.g. , benign , possibly damaging ) , using PolyPhen [85] and the Combined Annotation Dependent Depletion ( CADD ) scores [86] .
BEAGLE https://faculty.washington.edu/browning/beagle/b3.html#beaglev4 cnvHap http://www.imperial.ac.uk/people/l.coin CoNIFER http://conifer.sourceforge.net GEMINI http://faculty.washington.edu/wijsman/software.shtml MORGAN https://www.stat.washington.edu/thompson/Genepi/MORGAN/Morgan.shtml PBAP ( Pedigree Based Analysis Pipeline ) http://faculty.washington.edu/wijsman/software.shtml PEDSTATS http://csg.sph.umich.edu/abecasis/Pedstats/download/ PennCNV http://penncnv.openbioinformatics.org/en/latest/ PLINK http://pngu.mgh.harvard.edu/~purcell/plink/download.shtml
All statistical analyses were undertaken using Stata version 14.2 ( StataCorp , College Station , TX ) .
EthoVision settings for activity , distance and velocity analyses : Activity ( pixel change ) , distance moved ( m ) and velocity ( m / s ) were measured using an automated video - tracking and motion analysis program , EthoVision XT 10.0 ( Noldus IT , Netherlands ) .
In order to determine the most stable control genes over time and condition the GeNorm v 3.3 software was used [38] .
Stimuli were elaborated using the image processing toolbox on MATLAB ( Mathworks Inc . , Sherborn , MA , USA ) .
Stimuli were displayed using E - prime software ( E - prime Psychology Software Tools Inc . , Pittsburgh , USA ) on a computer monitor ( 17 - inch , with a resolution of 1024 × 768 pixel size , 75 Hz ) at a viewing distance of 73 cm .
Data Processing and Metabolite Identification : Following LC - QTOF - MS data acquisition , the acquired raw data files were processed with Agilent MassHunter Qualitative Analysis software ( version 5.0 ) .
The pre - processed data files were imported into Agilent Mass Profiler Professional software ( version 12.1 ) for further statistical analysis .
To identify statistical significant differences between the control and IUGR fetal brain tissue samples the processed data files were imported into Agilent Mass Profiler Professional software version 12.1 ( Agilent Technologies , Santa Clara , CA ) for statistical analysis .
Correlations between fetal birth weight and metabolite intensities were performed in Graphpad Prism version 5 ( GraphPad software , San Diego , CA ) .
Data analyses were conducted using STATA version 14 ( StataCorp , College Station , TX , USA ) .
All the analyses were carried out using STATA version 12.1 ( StataCorp . , College Station , TX , USA ) .
Statistical analysis was carried out using the Statistical Package for the Social Sciences , Release 17.0 ( SPSS Inc . , Chicago , IL ) .
SPSS version 11.5.1J software for Windows ( SPSS Inc . , Tokyo ) was used for the above statistical analyses .
All statistical analyses were performed with The Statistical Package for Social Sciences ver. 23.0 ( SPSS , Chicago , IL ) .
All follow - up measures were completed as part of a 60 - to 90 - minute computerized assessment battery programmed using Inquisit 4.0.8 , a psychological measurement software capable of being tailored to execute various types of assessments [65] .
For multiple imputation , we generated 25 multiply imputed datasets using the multivariate normal regression procedure in Stata 15.0 [90] .
After the algorithms were created , the 18 - month ASQ 3 scores and the Bayley - III scores were extracted from the medical charts and interpreted using a computer program created with R version 3.1 software [17] .
We then established the preliminary species assignment using NCBI ’ s BLAST search and we further confirmed this by aligning the sequences with in - house control sequences using the MEGA 5 software [34] .
In Uxpanapa , we later calculated the shortest distance to the nearest anthropogenic habitat ( pasture , plantation , orchard , etc . ) , shortest distance to the nearest human settlement , and the number of human settlements within a 2.5 km , 5 km and 10 km radius , using a classified 2008 Landsat satellite image ( 1 ∶ 20,000 scale ) of the study area , the ArcView GIS software ( version 3.1 ) , and the Patch Analyst 2.2 extension for ArcView [39] .
Statistical analysis was conducted using SAS v. 9.2 ( SAS Inc , Cary , NC , USA ) .
Image preprocessing and analyses were performed using statistical parametric mapping ( SPM 5 , Wellcome Department , London , UK ) that was run on a MATLAB 7 platform ( MathWorks , Natick , MA ) .
The statistical analysis of the phenanthrene degradation data were performed by a parametric one - way ANOVA test using the SigmaPlot / SigmaStat software program ( SPSS Inc . , Chicago , Illinois , USA ) .
The open reading frames ( ORFs ) were identified and automatically annotated using de Rapid Annotation using Subsystem Technology ( RAST , http://rast.nmpdr.org/ ) .
Putative functions of predicted ORFs were manually checked by BLASTp searches against all non - redundant protein sequences from the NCBI database and by functional analysis of deduced protein sequences using InterPro web service ( http://www.ebi.ac.uk/interpro/ ) , which allowed protein classification into families and predicted the presence of protein domains .
The software used for spectrum visualization and MS / MSMS protein identification was Flex Analysis ( v. 3.3 ) and BioTools ( Bruker Daltonics ) linked to MASCOT ( Matrix Science , Boston , MA 2016 ( http://www.matrixscience.com/ ) to search against the NCBInr protein sequence databases .
Genotypes were identified using GeneMapper V 4.0 . , with manual control of scored alleles , and assigned to family by the use of FAP Family Assignment Program v 3.6 [59] .
All statistical analysis was performed using R ver. 2.15.1 ( R Development Core Team ; www.r-project.org ) with critical P - values set to 0.05 , unless otherwise stated .
LMEs were fitted using the lmer function in the lme 4 package [72] , and Levene ’ s tests were performed using the leveneTest function in the car package [73] .
Heritability and additive genetic variance were estimated using the MCMCglmm package [74] , while the HPD intervals were calculated using the HPDinterval function in the lme 4 package [72] .
PLINK v 1.03 was used for the analysis [45] .
PCR - amplification primers were designed using Primer 3 ( http://frodo.wi.mit.edu/ ) with M13 Forward and Reverse Tails added to each primer to facilitate high - throughput DNA sequencing ( Table S8 ) .
Sequence data were imported as AB 1 files into Mutation Surveyor v 3.10 ( SoftGenetics , State College , PA ) .
Gene selection was performed using the UCSC Genome browser ( http://genome.ucsc.edu/ ) and literature review of articles published in PubMed ( http://www.ncbi.nlm.nih.gov/sites/entrez ) .
For the statistical analyses of the data in this study , the Statistical Package for the Social Sciences ( SPSS ) version 22 ( IBM Corp , Armonk , New York ) was used .
We used SPSS ( v. 18.0 ; SPSS Inc . , Chicago , IL , USA ) in data analyzing .
Stata 12 ( Stata Corp . , College Station , TX , USA ) was used for all statistical calculations .
Calculations were carried out using Stata v 13.1 [13] and the R - library glmnet [14]
To extract noun phrases to use as search terms for each of the papers on PubMed Central , we run a software program written in Python based NLTK ( http://www.nltk.org/ ) to automatically extract nouns , adjectives , and noun phrases from each sentence in the paper .
The theory of noun phrase extraction has been described in [22] and [20] , and noun phrase extraction is available in commercial software packages such as Attivio ( See < http://www.attivio.com/active-intelligence/aie-features/aie-language-processing.html > ) and Inxight ( See < http://www.inxightfedsys.com/pdfs/LinguistX_FinalWeb.pdf > ) .
The significance level was defined as p < .05 and the data were analyzed using SAS software version 9.1 ( SAS Institute Inc . , 2003 ) .
All statistical analyses were performed with SPSS for Windows version 21.0 ( IBM Corp . , Armonk , NY ) .
DNA sequence data were analyzed using SeqScape v. 2.5 software ( Applied Biosystems ) and compared with the revised Cambridge reference sequence ( rCRS ) [69] .
Descriptive statistical indexes , the Tajima ' s D [70] and Fu ' s FS [71] neutrality tests ( for HVS 1 sequence data ) were calculated using Arlequin software , version 3.01 [72] .
Principal Component ( PC ) analysis was performed using mtDNA haplogroup frequencies as input vectors by STATISTICA 6.0 software ( StatSoft , Inc . , USA ) .
Nonparametric multidimensional scaling ( MDS ) analysis based on FST statistics calculated from HVS 1 sequences was also performed using STATISTICA 6.0 software ( StatSoft , Inc . , USA ) to visualize relationships between Altaian Kazakhs and Barghuts studied and other Asian populations around .
The most - parsimonious trees of the complete mtDNA sequences were reconstructed manually , and verified by means of the Network 4.5.1.0 software [91] , and using mtPhyl 2.8.0.0 software ( http://eltsov.org ) , which is designed to reconstruct maximum parsimony phylogenetic trees .
This equipment contained an infrared photocell grid ( 32 emitter / detector pairs ) to measure locomotor activity with Digipro System Software ( v. 140 , AccuScan Instruments ) .
Wound size was measured by Adobe Acrobat Pro software [34] and expressed as the ratio of the wound area to the dot measurement , then as a ratio to the original wound size on Day 0 [34] .
Differences in wound closure , tissue masses , mRNA expression , flow cytometry , and scratch width were analyzed using repeated measures or 2 - way ANOVA with Statview version 5.0.1 software ( Scientific Computing , Cary , NC , USA ) .
Data analysis was done using Statistical Package for Social Sciences ( SPSS ) version 20 software .
NQuery Advisor by StatsSols version 3.0 was used to calculate sample size .
STATA 12.0 by StataCorp LLC was the statistical software used in the analysis .
Data were analyzed with the Statistical Package for Social Sciences ( IBM SPSS , version 21.0 , IBM Corp . , Armonk , NY ) .
All data were analyzed parametrically with Prism 5 statistical software ( GraphPad ) .
Med - PC IV software ( MedAssociates , Inc . ) controlled all chamber components .
Raw data from MedPC output files and paper training logs were imported , copied , or entered into Excel ( Microsoft Office 2007 ) .
Excel , Prism 5 ( GraphPad Software Inc . ) , and Adobe Illustrator CS 5 ( version 15.0.0 ) were used to create graphical representations of data ( depicted as mean ± s.e .m ) .
SPSS Statistics ( versions 17.0 and 19 ; IBM ) was used to perform general linear model procedures as appropriate .
Models were fitted using the open source R programming language [34] and the H2O R interface version 3.8.2.2 [35] that optimizes all the analytical methods used for large datasets .
The h2oEnsemble package version 0.1.8 [36] was used to fit the SL model .
The analysis took about 2.5 hours to run in a Windows 7 Professional desktop computer with 8 - core i7 - 3770 3.40 Ghz CPU and 8 Gb RAM .
AUC confidence intervals and variances were estimated using the Delong and colleagues methodology [37] as implemented in the R package pROC [38] .
The complete data were recorded with the software Microsoft Excel 2010 and then analysed with the statistical software IBM SPSS Statistics version 20 .
The maps were drawn from free - access shapefiles obtained from DIVA - GIS ( http://www.diva-gis.org/ ) with QGIS 1.8.0 and ArcView 3.2 software .
For neuroimaging data pre - processing we used standard FMRIB Software Library ( FSL ) tools v 5.0 ( http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/ ) [21] .
Brain tissues were segmented using FMRIB ' s Automated Segmentation Tool ( FAST ) that allows extracting measures of total grey matter ( GM ) , white matter ( WM ) and cerebrospinal fluid ( CSF ) [22] .
Fractional anisotropy ( FA ) , mean diffusivity ( MD ) , axial ( DA ) and radial diffusivity ( DA ) maps were generated using DTIFit , part of FMRIB ’ s Diffusion Toolbox , that fits a diffusion tensor model at each voxel [24] .
Resting - state fMRI data pre - processing consisted of motion correction , brain extraction , high - pass temporal filtering with a cut - off of 100 s , and field - map correction and was carried out using FSL Multivariate Exploratory Linear Optimized Decomposition into Independent Components ( MELODIC ) [25] .
To identify and regress out the “ signal ” of artefactual components reflecting non - neuronal fluctuations , we used single - subject independent component analysis ( ICA ) followed by an automatic component classification with FMRIB ' s ICA - based X - noiseifier ( FIX ) [ 26 , 27 ] .
FMRIB ’ s Integrated Registration and Segmentation Tool ( FIRST [30] ) , an automated model - based segmentation / registration tool , was applied to extract volumes of sub - cortical GM structures .
White matter integrity ( FA , MD , DA and DR ) was analysed using FMRIB ’ s Diffusion Toolbox and tract - based spatial statistics ( TBSS ) , a voxelwise approach for analysis of FA ( and MD , DA , DR ) data [31] .
For all image - based analyses ( VBM , TBSS , dual regression ) voxelwise general linear modelling ( GLM ) was applied using permutation nonparametric testing ( 5000 permutations ) and P < 0.05 correcting for multiple comparisons across space using threshold - free cluster enhancement ( TFCE ) [33] .
We used SPSS software version 23 ( SPSS Inc . , Chicago , USA ) for non - image - based statistical analyses and to compare volumes of subcortical structures .
Linkage disequilibrium between the two UCP 2 polymorphisms was determined using the online tool CubeX [34] ( http://www.oege.org/software/cubex/ ) .
Data were analysed using the statistical software Stata 12.0 ( StataCorp LP , TX , USA ) .
Stimuli were generated using the Psychophysics Toolbox 3.0.9 [12] running under Matlab R 2007b ( Mathworks Inc . , USA ) and presented at 60 Hz for 19 participants , and at 75 Hz for the remaining 7 participants on a CRT monitor ( SAMTRON 98 PDF , dimensions : 36.5 x 27.5cm , resolution : 1024 x 768 pixels ) at a viewing distance of 60 cm .
We report partial eta squared ( η p2 ) as measure of effect size ( SPSS 22.0 for Windows , IBM Corp . 2013 ) .
Parameters were optimised using the quasi - Newton Broyden - Fletcher - Goldfarb - Shanno minimisation algorithm as implemented in the HGF 4.0 toolbox ( distributed as part of the TAPAS toolbox , http://www.translationalneuromodeling.org/tapas/ ) .
For model level inference , we calculated exceedance probabilities ( i.e. , the probability that model A is better at explaining the observed data than model B ) using random effects Bayesian model selection [17] as implemented in SPM 12 ( http://www.fil.ion.ucl.ac.uk/spm/software/spm12/ ) .
The demonstration programs for our super - threshold visual phenomena were created in Adobe Flash CS 3 and were programmed in Actionscript 2 , a scripting language that is built into the Flash programming environment .
The sample size was calculated using the G * Power 3.1 software ( release 3.1.9.2 ; available from : http://www.gpower.hhu.de/ ) [27] to assess the null hypothesis of no difference in parasite load levels between different sampling sites within the CL ulcer .
Statistical analyses were performed under a 5 % significance level , using the GraphPad Prism v 5.02 software .
The data were recorded on a case form ( CRF ) , entered in iDataFax management ( Version 2014.1.0 ) , and analyzed using the Statistical Package for the Social Sciences ( SPSS , Chicago , IL , USA ) .
Statistical analysis was performed using GraphPad Prism Software , version 3.0 . ( GraphPad Software , Inc . , San Diego , CA ) .
Statistical analyses were performed using GraphPad Prism 4.0 for Windows ( GraphPad Software , San Diego California USA ) .
Similarity among diets was evaluated using the clustering technique with the unweighted pair - group method and arithmetic averaging ( UPGMA ) based on the proportion of each prey type using the Morisita ’ s index on software PAST 2.17c [21] .
Major axes of dietary variation among the small cat species were identified through a correspondence analysis on software PAST 2.17c [21] .
Statistical analyses were conducted applying Statistical Program for the Social Sciences ( SPSS ) , version 24 ( IBM Inc . Chicago , IL , USA ) .
Genetic Ancestry and Social Classification : Three independent methods were used to estimate individual genetic ancestry : two Bayesian approaches using a Markov chain Monte Carlo algorithm , implemented in Structure 2.2 [71] and ADMIXMAP [72] , and a maximum likelihood method [73] implemented in software provided by Xianyun Mao .
The clinical assessment and laboratory results that were recorded into a Microsoft Access database were analyzed using Statistical Package for the Social Sciences ( PASW - former SPSS ) version 18 and R version 2.9.2 ( R Foundation for Statistical Computing , Vienna , Austria ) .
The statistical analyses were performed with IBM SPSS 20 .
We carried out data analysis in R v. 3.2.1 ( R Development Core Team , 2013 ) .
All analyses were performed using SAS , release 9.4 ( SAS Inc . Cary , NC , USA ) and SUDAAN , release 11.0.1 ( Research Triangle Institute , Research Triangle Park , NC , USA ) .
Statistical analysis was performed using Review Manager 5.3 ( Cochrane Collaboration , London , UK ) .
All analyses were performed using SAS version 9.2 ( SAS Institute Inc . USA ) .
All analyses were performed using the Statistical Package for Social Sciences software program , version 16 ( SPSS , Inc . , Chicago , IL , USA ) .
We analyzed the data using the statistical package for social sciences ( SPSS 12 ) .
All analyses were conducted using SPSS version 24.0J ( IBM Japan , Tokyo , Japan ) .
All statistical analysis was conducted in Minitab 16 ( Minitab Ltd ) .
SAS version 9.2 was used for all analyses ( SAS Institute Inc . , Cary , NC , USA , 2000 - 2008 ) .
All regression analyses were performed using SPSS Statistics 19 [37] with a significance level at 0.05 and 95 percent confidence intervals .
All statistical analysis was conducted using SPSS v. 18.0 ( IBM Corp . , Armonk , NY , USA ) .
Analyses were performed using Stata version 13.0 ( Stata Corp , College Station , Texas ) .
GraphPad Prism 5.02 was used for statistical calculations .
SPSS Statistics 20.0.0 statistical software ( SPSS Inc . , Chicago , IL ) was used for all statistical analyses .
The data were prepared for analysis using Stata v 13 [48] and the structural equation models were estimated using Mplus v 7 [46] .
All the statistical analyses were implemented with the statistical software SAS 9.2 [21] .
Descriptive statistics of survey data were performed in STATA ( Version 13 ; STATA Corp , College Station , TX , USA ) .
Finally , mediation models of the mismatch effect were tested with path analysis using PROCESS v 2.13 , a macro created by [51] for SPSS .
Data analysis in EEGLAB [31] and Mathworks Matlab involved band - pass filtering the EEG data between 0.5 Hz and 80 Hz , with a notch - filter between 45 and 55 Hz .
All statistical analyses were performed using IBM SPSS Statistics v. 22 .
We used the Brain Connectivity Toolbox [17] and MATLAB custom - made scripts to explore global and local topological properties of the ToM - network in each participant ’ s brain .
Statistical analyses were conducted by using SAS software , version 9.3 [ PROC GENMOD , with options REPEATED , CORR = IND , and DIST = NORMAL ; SAS Institute , Inc . , Cary , NC ] .
Multilevel regression analyses were performed in SAS software version 9.2 ( SAS Institute Inc . , 2009 ) .
We used IBM SPSS 22.0 for the quantitative analysis .
All statistical analyses were performed in STATA version 14 [46] .
All analyses were performed using STATA 11 ( Stata Corporation , College Station , TX , U.S .A . )
The models were estimated using MLwiN 2.25 software from within Stata 13 software , using the user - written subroutine ' runmlwin ' , and Markov Chain Monte Carlo ( MCMC ) methods [49] .
Statistical analyses were performed using JAGS Gibbs - sampling environment [43] and R 3.0.3 [44] .
Data were analyzed using GraphPad Prism version 6.0f for Mac OS X , ( GraphPad Software , La Jolla California USA , www.graphpad.com ) .
All analyses were performed using Stata 12.0 SE .
Analyses were conducted in STATA / IC 14 with individuals as the unit of analysis .
Data were entered using EpiData 3.0 and all statistical analyses were performed using SPSS 10.01 .
All analyses were conducted using IBM SPSS Statistics , Version 22 with weighted data .
To create a set of control stimuli that retained acoustic correspondence , we synthesized nonvocal sounds by using Praat [44] and MATLAB ( The MathWorks , Inc . , Natick , MA , USA ) .
All data obtained from the communities were recorded using EPI INFO version 5 ( CDC , Atlanta ) and imported into Microsoft Excel .
Statistical analyses were performed in SPSS 19.0 and R 3.0.1 [42] .
All statistical analyses were performed with the aid of SPSS software version 22.0 ( IBM Co . , Armonk , NY , USA ) .
Data was analyzed using IBM SPSS Statistics 18.0 .
Survey responses were analyzed using STATA 15 [16] .
All analyses were conducted using Stata 12.1 [44] .
The quantitative data were analyzed using descriptive statistical analysis , correlations , and binominal logistics regressions on IBM SPSS Statistics 18 ( Forward : LR method ) , and applying Latent Class Modeling ( LCM ) on LatentGold 3 .
All statistical analyses were performed using the SPSS 19.0 software package ( SPSS Inc . , Chicago , IL , USA ) .P - values < 0.05 were considered statistically significant .
All the analyses were performed using STATA 13.1 ( StataCorp . , TX , USA ) .
SPSS version 16 for Mac OS 10.5 was used to run the linear mixed effect models , significance levels were set at 0.05 , and two - tailed probability values are quoted .
Analyses were conducted using SPSS version 22.0 statistical software packages ( SPSS , Chicago IL , USA ) .
Statistical analyses were conducted using GraphPad InStat version 3.10 ( GraphPad Software , Inc . , La Jolla , CA , USA ) .
Data analysis was conducted using SigmaStat 3.5 and SPSS for Windows 11.5 .
Data were analysed using SPSS 15.0 for Windows .
Statistical analyses were performed using PASW Statistics version 18 for Windows ( SPSS Inc . ) .
SPSS software ( IBM SPSS statistics version 21 ) was used for statistical analyses .
Data were analysed using SPSS version 22 [48] .
Crude and adjusted relative risks ( RR ) for dependence at 12 , 24 and 36 months were statistically assessed by Poisson regression model using Statistical Analysis System software version 9.2 with PROC GENMOD ( SAS Institute Inc , Cary , NC ) [21,22] .
Data analyses were conducted using the SAS software version 9.1 ( SAS , 2004 ) and SUDAAN ( Research Triangle Institute , 2004 ) .
All statistical analyses were conducted with SPSS ( v. 20.0.0.2 ) and R ( v. 3.1.3 ) .
All analyses were performed using STATA / SE 10.1 ( StataCorp , College Station , TX , USA ) .
All analyses were performed with SPSS for Windows ( SPSS , version 23 ; Chicago , IL , USA ) , and p values < 0.05 ( two - way ) were considered to indicate statistical significance .
Statistical analyses were conducted using SAS software , version 9.3 ( PROC GENMOD , with options REPEATED , CORR = IND , DIST = BINOMIAL , LINK = LOGIT ; SAS Institute , Inc . , Cary , NC ) , and a P < 0.05 was considered statistically significant .
Statistical analysis was carried out using STATA 11.2 [18] .
Convenient integration between Matlab and Google Cloud was achieved through using a software called Techila Technologies .
formtok linear trend of time series signals ( x ( t ) and y ( t ) ) was excluded using the “ detrend ” function of MATLAB ( The MathWorks Inc , USA ) and the signals were filtered using Hanning windows of the same size as the data length before their cross correlation was calculated ( the MATLAB ’ s “ detrend ” function computes the least - squares fit of a straight line to the data in question and subtracts the resulting function from the data ) .
Data was analysed using STATA 11.2 [44] .
The simulations were run in Excel from Microsoft Office .
Data analysis was performed using the Statistical Package for the Social Sciences ( SPSS for Windows , version 19.0 , SPSS Inc , Chicago , IL , USA ) and included frequency distribution and association tests .
All previously published Vg sequences plus Vg sequences obtained by BLAST searches were used to construct an alignment using the web - based Clustal Omega tool ( https://www.ebi.ac.uk/Tools/msa/clustalo/ ) .
All statistical analysis was carried out with STATA 12.0 , Statacorp , College Station , Texas , USA .
All statistical modeling and analyses were conducted using PASW Statistics 18 , Release Version 18.0.0 ( SPSS , Inc . , 2009 , Chicago , IL , www.spss.com ) .
All statistics were performed in STATA ™ / MP 13 software .
Data are presented as ( Mean ± SEM ) and were analysed with IBM SPSS 22.0 software .
All analyses were performed using Stata 14.2 [36] .
All statistical analyses were conducted using IBM SPSS Statistics 21 .
All data analyses were computed using SPSS 13.0 and AMOS 17.0 .
[72] , probes not rated as “ perfect ” ( 50 out of 50 nucleotides match the reference genome ) or “ good ” ( 48 to 49 out of 50 matches to the genome ) were removed ; so were probes that mapped to more than one genomic location according to BLAST queries [73] and probes that included a SNP ( NCBI dbSNP Build 137 ) ; finally , only probes detected in at least 5 % of the mice at a 0.95 detection level ( as per GenomeStudio ) were retained .
All HB analyses used WinBugs 1.4 , available from ( http://www.mrc-bsu.cam.ac.uk/bugs/ ) , and the R 2WinBUGS package version 2.1 - 16 .
Analyses were conducted with SAS software Version 9.2 [30] , and SUDAAN software Release 10.0 [31] , and incorporated weighting to account for sampling design .
Off - line EEG processing and analyses were performed by adopting custom MATLAB ( MathWorks ) scripts using functions from the EEGLAB environment [38] .
All statistical analyses were conducted using IBM SPSS , Version 22 .
Data were edited , coded and entered using EPI Info version 3.02 and then transferred to Stata version 14.2 for statistical analysis .
The normality tests , repeated measures and multivariate ANOVAs , Student t - test ( two - tailed ) and Mann - Withney analysis were done using SPSS statistic 19.0 ( IBM ) .
Linear regression analyses were performed using statistical analyses software ( SAS 9 ) version 9.2 ( SAS Institute , Cary , NC ) .
All analyses were performed using SPSS 19 ( IBM SPSS Statistics 19.0.0 ) .
All analyses were conducted using statistical software STATA 14 ( StataCorp , 2009 ) .
Models were run using the MATLAB routine REGRESSIONv 2.m described in [54] .
All analyses were performed using STATA version 14.1 ( Stata Corporation , College Station , TX , USA ) with survey ( SVY ) commands for the adjustment of the cluster sampling survey design .
All analyses were performed with statistical software STATA version 9.0 ( StataCorp , College Station , TX ) .
All statistical analyses that include independent samples t - tests , Cohen ' s effect size value , Pearson correlations , one - way analysis of variance ( ANOVA ) and 3 * 2 mixed - design , ANOVA were performed on the Software Package for Statistical Analysis ( SPSS for Windows version 19.0 ) , [24] .
This negative binomial mixed model regression was run using Stata 13.0 ( StatCorp , College Station , TX ) .
The analyses were run using STATA MP 11.2 .
All data were analyzed using SPSS statistical software ( version 21.0J ; IBM SPSS Japan , Tokyo , Japan ) .
All analyses were performed using the ESRI ™ suite of ArcGIS 10.3 software and Stata / SE Software version 12.1 for Windows ™ .
The data were analyzed using the Statistical Package for the Social Science ( SPSS ) , version 17.0 .
For statistical analyses , the software package SPSS 18.0 ( SPSS Inc . , Chicago , IL , USA ) was used .
Data were analyzed with SPSS ( version 19 , SPSS Inc . , Chicago , Illinois ) and NCSS 2007 ( Number Cruncher Statistical Systems , Utah , USA ) statistical software packages .
All the other analyses were performed with SPSS version 17.0 ( SPSS Inc . , Chicago , IL , USA ) .
MNI coordinates for the channels were obtained using the NIRS _ SPM software [40] with MATLAB ( Mathworks , Natick , MA ) , and the corresponding anatomical locations of each channel were determined by the atlas provided [ 41 , 42 ] and shown in S1 Table .
Regression backward model selection was conducted , using IBM SPSS Statistics v 20.0 package [94] to fit each model .
Data management and univariable analyses were performed in STATA version 11 ( StataCorp LP , College Station , Texas , United States of America ) .
The statistical calculations were performed using GraphPad Prism version 5.03 for Windows ( GraphPad Software , San Diego , USA ) .
All statistical analyses were conducted using the SPSS version 17.0 ( IBM Inc . , Armonk , NY , USA ) .
All analyses were done using SPSS Software for Windows ( v. 15 IBM , Chicago , IL , USA , ) and graphs were drawn using Sigma plot for Windows ( v. 8.02 . Systat Software Inc . , San Jose , CA , U.S .A . ) .
SPSS 18.0 and Mplus 7.0 ( using an exploratory LPA ) were used to analyze the data .
The analyses were conducted in IBM SPSS Statistics 21 Advanced Model .
All data analysis was performed offline in MATLAB environment ( version R 2010a , The MathWorks , Natick , MA ) in a way that will allow later straightforward automatization of the analytic procedure .
All statistical analyses were performed using SAS System for Windows version 9.3 ( SAS Institute , Cary , NC ) .
This was performed using the svyset and svy commands in Stata Version 12.1 ( StataCorp , 4905 Lakeway Drive , College Station , Texas 77845 , USA ) .
Data analysis was conducted using SigmaPlot ver. 12.3 ( SYSTAT Software Inc . , San Jose , CA , USA ) .
Quantitative data were analyzed using the Statistical Analysis System ( SAS ) ( version 9.4 , SAS Institute Inc . ) .
All statistical analyses were performed using STATA version 12 ( STATA Corp , College Station , TX ) .
Analyses were carried out using SPSS v 18 ( SPSS inc , Chicago , USA ) and SAS v 9.2 ( SAS , Cary , North Carolina , USA ) .
Statistical analyses were performed using Prism v. 6.0 ( GraphPad Software , Inc . , La Jolla , CA ) and SPSS software ( Chicago , IL ) , with a significance level of p < 0.05 .
All regression analyses were conducted using Proc Glimmix in SAS 9.3 ( SAS Institute , Cary , NC , USA ) .
The hypothesized relationships were assessed using the PROCESS macro for SPSS [62] with Model 5 , which estimates the indirect effect of X ( Job characteristics ) on Y ( Psychological Work Ability / Job mobility Intentions ) through the mediator M ( Motivational Orientations ) , with a moderating role played by W ( Age ) in the X → Y ( Job characteristics → Psychological Work Ability / Job mobility Intentions ) relationship .
The statistical package for social science 18.0 ( SPSS 18.0 ) program was used for statistical analysis .
Data were analysed with IBM SPSS version 22.0 for Windows .
Instead , we applied a custom built MATLAB routine ( using the speech processing toolbox ‘ voicebox ’ in MATLAB v. R 2014a ) to extract acoustic ‘ features ’ ( mel - frequency cepstral coefficients ; MFCCs ) from single screams and chorus excerpts .
All statistical tests were performed with SPSS ( version 21 , SPSS Inc . , Chicago , IL , U.S .A . ) .
Analyses were conducted using STATA 13 / SE ; [28] sample weights were used to account for the MCS complex survey design and cohort attrition over time .
All statistical analyses were carried out using GraphPad Prism version 5.04 for Windows , GraphPad Software , San Diego , CA , www.graphpad.com.
Multilevel mixed effects logistic regression ( xtmelogit ) on the 3 sexual risk behaviour indicators were analysed using STATA 11.1 ( StataCorp , 2009 ) .
The analyses were performed using STATA v 14 ( StataCorp , College Station , TX ) .
Then , the hypotheses were tested with OLS Ordinary Least Square through the PROCESS macro for SPSS , which assesses the conditional indirect effects [38] .
Analysis was then done by one researcher ( SS ) using MSOffice ( Word and Excel , Microsoft Corp . ) and NVivo ( QSR International ) software for qualitative data analysis .
For the Alternating EE paradigm , statistical analyses were performed using SAS 9.3 statistical analysis software ( SAS Institute ) .
The data were tabulated and analyzed using software Epi - Info version 3.5.2 and SPSS version 19 .
Data processing and statistical analyses were conducted using IBM SPSS 22.0 ( IBM Corp . , Armonk , NY ) , MATLAB R 2015a ( The MathWorks , Natick , MA ) , R 3.3.2 ( http://www.R-project.org/ ) , and Python libraries for scientific computation ( NumPy , and SciPy ) [39] .
The ANOVAs and linear contrasts were performed with SAS version 8.1 ( SAS Institute Inc . ) , while the correlation analyses were performed with JMP ( SAS Institute Inc . ) .
We built a generalized linear mixed model ( GLMM ) using the GLIMMIX procedure [43] in SAS v 9.3 to identify factors associated with the occurrence of groups .
All statistical analyses were done in Stata 12 ( Stata Corp . Inc . TX , USA ) .
Statistics were carried out using PASW Statistic 18 software ( SPSS Inc . , Chicago , IL , USA ) .
The statistical analyses were carried out using IBM SPSS 22 for Windows ( IBM Corp . Released 2013 ) .
All analyses were conducted using SPSS Version 15.0 for Windows .
The analyses were conducted using the SPSS statistical software program ( PASW 18.0 ) .
Statistical analyses were performed using Statistical Package for the Social Sciences ( SPSS ) Version 19.0 software ( IBM Corp , Armonk , NY ) .
Statistical analysis was performed using the IBM SPSS Statistics 20 ( IBM Inc . , Chicago , IL ) .
All statistical analyses were conducted using Statistical Package for Social Sciences ( SPSS 20.0 ) .
Mediation analysis was carried out with the commands “ binary _ mediation “ and “ bootstrap ” in Stata 13 [52] .
All analyses were conducted using PASW Statistics 18 ( SPSS Inc . , 2009 , Chicago , IL , USA ) and were two - tailed with a critical p - value of 0.05 .
We used the Statistical Package for Social Sciences ( SPSS for Windows , version 16.0 , SPSS Inc . , Chicago , IL ) in the statistical analyses process .
All analyses were performed using R version 3.2.4 ( Vienna , Austria ) and STATA version 14 ( College Station , Texas ) .
Statistical analyses were performed using SPSS v 15.0 ( SPSS , Inc . , Chicago , Illinois , USA ) and Intercooled Stata 10 ( StataCorp LP , College Station , Texas , USA ) software packages .
All statistic analyses were computed using Statistical Package for Social Science ( SPSS , Chicago , Illinois , USA ) software version 19.0 for Windows .
Information was double entered using Microsoft Excel for Windows , and then transferred to STATA version 12 ( STATA Corp , College Station , TX , US ) for analysis .
The data was analyzed using SPSS ™ version 17.0 ( SPSS Inc . , Chicago , IL , USA ) for Windows ™ .
Repeatability was determined using the intraclass correlation coefficient ( τ ) , obtained from an analysis of variance ( ANOVA , implemented in SAS version 9.1 ( SAS Institute Inc . , Cary , NC , USA ) ) and the equation for repeatability [32] .
Descriptive and regression analyses were performed by using STATA statistical software v. 14.1 ( STATA Corp . , College Station , TX , USA ) .
Receipt of QAC data was acknowledged , entered into a password - protected Microsoft Access database , and cross - checked through Microsoft Excel .
We used a Matlab implementation of the SPIKE - dist measure ( http://wwwold.fi.isc.cnr.it/users/thomas.kreuz/sourcecode.html ) , with a temporal resolution of 1ms , to analyze our data .
Statistical analysis was undertaken using the Statistical Package for Social Sciences ( SPSS ) for Windows , version 21 .
Associations with teenage motherhood were modeled using multilevel logistic regression of the above structure using STATA MP statistical package version 14 ( StataCorp L , College Station , Texas , USA ) .
Statistical analyses were performed with SigmaPlot 11.0 ( Systat , Inc . , San Jose , CA . )
The data were analysed using Statistical Analysis Systems ( SAS ) version 9.2 .
These data were analysed using SPSS ( version 21 ) for Windows .
STATA version 11.2 software ( STATA Corp , College Station , TX , US ) was employed for our analyses .
Analyses were conducted using SPSS version 24.0 and R .
Measurement model analysis was conducted using AMOS 23 , whereas the remaining analyses were computed using SPSS 23 .
All analyses were undertaken using the IBM SPSS 22 software .
Data were analyzed using SAS ™ 9.2 and STATA ™ 12 statistical software ™ .
Outcomes were analyzed using unweighted linear or logistic regression ( SAS / STAT software , version 9.2 ) .
Statistical analysis was performed using SAS 9.3 ( SAS Institute , Cary NC ) .
All analyses were performed using Stata / SE 11.2 software for Mac ( R ) .
A PCA analysis was conducted using XLSTAT 2015 for Excel .
We carried out all our analyses using Stata 12 [50] .
The data were manually entered into a database and analysed using the Statistical Package for the Social Sciences software ( IBM SPSS Statistics 18 ) .
Apart from Microsoft Excel [20] used to manage qualitative data , the statistical software Stata version 12 [21] was used to generate Table 1 .
Statistical analysis was performed using GraphPad Prism ( version 4.0 ) and SPSS ( version 20 ) .
Correlation coefficients were calculated with SPSS software version 21 [61] utilising the bivariate Pearson two - tailed analysis .
Statistical tests were carried out using SPSS 16.0 ( SPSS Inc . , Chicago , IL ) for Windows .
Data were analyzed in Microsoft Excel 10.0 ( Microsoft , Redmond , WA ) and STATA / IC 12.1 ( Stata Corp , College Station , TX ) .
The data were analyzed using SPSS software ( Statistical Package for the Social Sciences , version 17.0 ) .
The IBM Statistical Package for the Social Sciences ( SPSS - 22 ) software was used to analyze the quantitative data .
The data was analysed using EpiData Analysis software ( Version 3.1.80 ) and Stata ( Version 12 ) .
All analyses utilized weighted data proportional to sampling probability with village , GV , and health facility cluster weights ; standard errors were computed using SAS 9.3 and STATA 14 procedures to account for the complex sampling design .
We used the AMOS extension to IBM SPSS ( v. 21.0 ) for structural equation modeling in order to identify associations of AR CAG repeat number , ethnicity and age with the number of children , mediated through BPAQ aggression scores .
Statistical analyses were performed in STATA ( version 12.1 , Stata Corp , College Station , TX ) .
The data were analyzed with SPSS software ( IBM SPSS Statistics for Windows version 22.0 , Armonk , NY : IBM Corp . , under license to the Central Computer System of the University of Malaga , Spain ) .
Data were analysed using STATA 12.0 ( Stata Corp , College Station , TX , USA ) .
Data analyses were conducted using the SPSS 16.0 software package ( SPSS Inc . Chicago , USA ) .
For this , the statistical program SPSS ( Statistical Package for Social Sciences ) for Windows version 19 was used .
Statistical analyses were performed using SPSS for Windows software version 15.0 ( SPSS Inc . , Chicago , IL ) .
Preprocessing and statistical analysis of the fMRI data was performed with SPM 8 ( Wellcome Department of Cognitive Neurology , London UK ) software for MATLAB ( Version R 2010a , The MathWorks Inc . , Natick , MA ) .
All statistical analyses were performed with SAS software version 9.3 ( SAS Institute Inc , Cary , NC ) .
The above analyses were performed in Stata 13 statistical software [32] .
All three stages of analysis were conducted using SPSS software ( IBM SPSS Statistics 20 , IBM Corporation ) .
Statistical analysis was performed with SPSS version 20 software ( IBM Corporation , Armonk , New York , USA ) .
All statistical tests were performed with GraphPad Prism ™ 4 .
Graphs and statistical analysis were conducted by SPSS 17.0 and Excel 2007 .
For each participant , mean amplitudes of the components of interest ( see above ) were exported and read into SPSS ( version 21 , IBM ) .
All statistical analyses were performed using the SAS software version 9.4 ( SAS Institute , Cary , NC , USA ) .
The statistical software IBM SPSS Statistics version 22 [39] and R [40] were used for the statistical analyses .
All statistical analyses were performed with SAS ( V 9.1.3 ) on a Win 7 ( 64 bit ) platform .
Initial descriptive statistics were calculated in MS Excel ™ , with subsequent statistical analysis conducted using IBM SPSS Statistics v 22 ™ .
We classified each sequence at the family level , and used blast [36] to identify those OTUs that had been previously found in bees ( blastn , e - value < 0.0001 ) .
Stimulus presentation and timing of all stimuli and response events were achieved using Matlab ( Mathworks ) and Psychtoolbox ( www.psychtoolbox.org ) on an IBM - compatible PC .
The user - written ice commands [35] - [41] in Stata v 11.2 ( Stata Corp , TX , USA ) were used to complete five imputations with ten cycles in each imputation .
The visual stimuli were generated using Psychophysics toolbox [49-51] in MATLAB ( The MathWorks Inc . , Natick , MA ) .
One - way ANOVAs were used to test combined drug treatment and prenatal exposure effects on oxygen consumption and CO 2 production ( GraphPad Prism 5.0 d ) .
All analyses were performed using SAS v. 9.2 [34] .
STATA ( StataCorp , College Station , TX , USA ) , version IC 13.1 , was used in all the statistical analyses .
Data were double - entered into a predesigned EpiData 3.1 database with validation checks , and exported to Stata 10.0 for analysis .
All analyses accounted for complex survey design using SUDAAN 11.0 ( RTI , Research Triangle Park , North Carolina ) and were weighted to account for the selection of HCHS / SOL participants with unequal probabilities [24] and were performed using SAS version 9.3 ( SAS Institute , Cary , NC ) and SUDAAN release 11.0.1 ( RTI International , Research Triangle Park , NC ) .
All analyses were performed using Stata 13.1 software [30] .
All data was analyzed using SPSS 14.0J ( SPSS Inc . , Chicago , IL ) statistical package .
In our study , it was calculated by fitting model 2 to the first set of imputed data and then using the punafcc package in STATA 14 .
Data were analyzed using IBM SPSS Statistics version : 20 .
All analyses were carried out in R ( version 2.8.0 ) and Matlab ( version 2009b ) .
All quantified regions were analyzed by Multivariate Analysis of Variance ( MANOVA ) for main effects of genotype , competition dose , and genotype x dose interactions using IBM SPSS Statistics 22 .
The statistical packages SPSS 15.1 and STATA 11.1 were used to carry out the analyses .
To analyze associations between individual and environmental variables and walking for transportation , we estimated several multilevel logit ordinal regression models using the Dual Quasi - Newton optimization estimation approach of Proc Glimmix in SAS 9.3 ( SAS Institute Inc . , Cary , North Carolina ) .
All data were analysed using the IBM SPSS Statistics 22 ( IBM , NY , USA ) software package .
All data were analyzed with SPSS version 21.0 [34] .
A multiple linear regression was conducted to isolate independent predictors of nutritional outcomes of child using SPSS version 21 windows software .
Generalized Linear Mixed Models ( GLMM ) analyses were conducted , using IBM SPSS Statistics , Version 25 , to examine the effects of tDCS on patients ’ performance on social cognitive , neurocognitive , and EEG measures .
All statistical analyses were carried out by using PASW Statistics 18 ( SPSS Inc . , Chicago , IL ) .
Statistical analyses were computed using SPSS version 19.0.1 ( IBM , Somers , NY ) and the plot was generated using Prism version 5.0d ( GraphPad , La Jolla , CA ) .
Text files of the R - R interval data were extracted from the Polar watch and were entered into Kubios HRV ( version 2.0 , 2008 , biosignal analysis and medical imaging group , University of Kuopio , Finland , MATLAB ) .
The analyses were conducted by using the PROCESS macro written by Andrew F . Hayes [38] , which can be implemented in SPSS , and it is based on an ordinary least squares regression .
All analyses were performed using SPSS for Windows version 23 software ( IBM Japan Ltd , Tokyo , Japan ) .
Offline filtering and heart beat detection were also conducted in AcqKnowledge before the data were exported into SPSS ( Version 23 , IBM Corp , USA , NY ) .
All statistical analyses were performed with the Mplus statistical package version 7.3 and IBM SPSS version 22 .
Analyses were performed using the SPSS Windows Version 20 [33] .
All analyses were conducted using SAS version 9.1.3 ( SAS Institute , Cary , North Carolina , U.S .A . ) .
We carried out the analyses using SPSS 10.0 ( SPSS Inc . , Chicago , IL , USA ) .
To allocate the participants into two groups ( intervention / experimental and control ) , we used SPSS ( IBM v. 23 ) random sampling software .
All the statistical analyses were carried out with IBM SPSS Statistics 19 .
SPSS for windows version 20.0 was used .
Statistical analysis was performed using Excel ( Microsoft ) and OriginPro ver 7.5 ( OriginLab ) .
Microsoft Excel and Statistical Package for the Social Sciences ( SPSS Version 22.0 ; Chicago , IL , USA ) were used for all data analysis .
We accessed the data using the visualization and data analytics software Tableau , and prepared data for analyses in both Tableau and Excel ( Tableau 9.0 , Tableau Software Inc . ; Excel 14.4.2 , Microsoft Corporation 2010 ) .
The results are presented as a set of predicted probabilities of being fully immunized , estimated using logistic regression post - estimation command available in Stata 10.0 [52] .
SPSS 23 ( IBM , Armonk , New York ) was used for all analyses .
All analyses were performed using SPSS ( Version 22 , release 22.0.0.2 , IBM Corp . , USA ) .
All analyses were performed with multiple imputation methods using STATA version 14 ( Stata Corp LP , College Station , TX , USA ) .
Analysis of local scale data across all crime types and the two counties ( Nottinghamshire and Derbyshire ) was done using general regression analysis applied to the log transformed mean and variance values with categorical variables using commercially available software ( Minitab version 16.2 ; Minitab Inc . ) .
All statistical analyses were conducted using SPSS Statistics 23.0 and AMOS version 23.0 .
All statistical analyses were performed using SPSS version 19 ( IBM Corp . , Armonk , NY ) .
Descriptive statistics were performed using Graphpad Prism 6 .
We used the SAS system ( version 9.3 SAS Institute Inc . ) for statistical analysis .
Data analyses were conducted with IBM SPSS statistics , version 20 .
LCGM was performed in STATA ( version 12.1 , College Station , TX ) using the traj procedure [24] .
Consistent with Resibois , Verduyn , and colleagues [11] , each of the obtained 384 self - reported intensity profiles following negative feedback was first transformed into a function using the linear interpolation function ( interp 1 ) implemented in MATLAB R 2016b [38] and then discretised into 44 equally distanced time points , corresponding to the number of images acquired during the period that participants read and thought about the feedback .
These time series were subsequently decomposed into two components using non - negative matrix factorization [39] ( as implemented in MATLAB R 2016b [38] ) .
All analyses ( except repeatability calculations ) were run using JMP 9 ( SAS Institute , Cary , NC ) and we analyzed residuals to assess violation of ANOVA assumptions .
The data were managed and analyzed using the statistical software package SPSS ( Version 18.0 for Windows SPSS , Inc . , Chicago , Ill ) .
All statistical analyses were performed using the statistical package SAS , version 9.1 ( SAS Institute , Inc . , Cary , North Carolina ) .
The automatic classification was performed in MathWorks Matlab , using the PRTools toolbox [57] .
Data were entered into excel ( Microsoft 2010 ) database and analysed using excel functions .
We used SAS 9.4 ( SAS Institute , Cary , NC , USA ) for data set - up and analyses .
Structural equation modeling was conducted using IBM SPSS Amos 21.0 .
The x - y coordinates of the individual positions were extracted using the Ctrax software ( Caltech Multiple Fly Tracker ; version 0.3.12 ) and the associated FixErrors toolbox for MATLAB ( v. 7.10.0 2010 ; MathWorks , Inc . , Natick , MA , USA [34-35] ; MATLAB v. 7.10.0 ) .
All statistical tests were analysed using IBM SPSS version 22 .
Further analyses regarding behavioural data ( t - test for paired samples ) were carried out using SPSS 11 ( SPSS Inc . , Chicago , USA ) .
All further statistical analyses ( t - tests for dependent samples ) were calculated using the software package SPSS 11.5 ( SPSS Inc . , Chicago , USA ) .
We used the cp _ apr function in the Matlab Tensor Toolbox [18] .
We therefore used Multiple Imputation with 5 imputations applying a set seed using the ice package in Stata version 11.2 , to ensure that our analysis would provide unbiased estimates .
All statistical analyses were performed using SPSS 15.0.1 for Windows ( SPSS Inc . , Chicago , IL , USA , 2006 ) .
We performed all analysis using SAS statistical software , version 9.2 ( SAS Institute Inc , Cary , NC ) .
Total intracranial volume was obtained by summing up the overall volumes of grey matter , white matter , and CSF , which were calculated by means of the MATLAB script “ get _ totals ” provided by Ridgway [77] .
Studies were exported to remove the duplicates in Refworks ™ and then exported to Microsoft Excel .
Data were analyzed using SAS version 9.4 ( SAS Institute , Carey , NC ) .
Statistical analyses were performed using SPSS 20.0.0 , except McNemar tests that were performed in R 3.0.0 [44] .
All analyses were performed with SPSS ™ for Windows version 21 .
The Gannet GABA analysis toolkit for Matlab was used to analyse GABA data [41] .
The MCMC simulation was conducted using the package rjags under R 3.0.3 and JAGS v 3.3.0 ( further technical details are provided in the Supporting Information ) .
Stimuli were presented using the Cogent 2000 toolbox ( http://www.vislab.ucl.ac.uk/cogent.php ) for MATLAB ( The Mathworks Inc . ) on LCD - goggles ( Resonance Technology Inc . ) .
MRI data was analyzed using SPSS Statistics ( IBM , version 19 ) using a generalized linear model fitted to a gamma distribution , with MAM treatment , enrichment , and gender as factors .
All statistical procedures were completed using SPSS 16.0 ( SPSS , Chicago , IL , USA ) .
All statistical analyses were conducted using SAS 9.3 software package ( SAS Institute , Cary , NC , USA ) .
All graph algorithms used in this article were implemented in Matlab and are available as part of the Brain Connectivity Toolbox ( www.brain-connectivity-toolbox.net ) [17] .
All statistical analyses were performed using STATA ™ version 10.0 and R Studio version 3.2.2 for Macintosh ™ .
All statistical analyses were carried out with SAS , version 9.3 ( SAS Institute Inc . , Cary , NC ) except for meta - analyses , which were performed using Comprehensive Meta - Analysis Version 2.2.027 software ( Biostat , Englewood , NJ ) .
Then , one village was randomly selected from each sub - county , using a random number generator ( Microsoft Excel Basic 2003 , Redmond , WA ) .
Then , we conducted one - way analyses of variance ( ANOVA ) with Dunnett ’ s test or T3 tests using SPSS 12 for Windows ™ ( SPSS , Chicago , IL , USA ) to determine significant differences between the control and VPA exposure groups .
All images were acquired through the Matlab Image Acquisition Toolbox ( Mathworks , Matlab v 2011b ) at 2 frames / s ( 500 ms exposure ) at 360x 260 pixel ( px ) resolutions ( using 4x 4 hardware binning ) .
The images were subsequently processed and analyzed on a pixel - by - pixel basis using the Matlab Image Processing Toolbox ( Mathworks , Matlab v 2011b ) using script modified from Theyel and colleagues [20] .
Statistically significant moderation paths ( see Fig 2 ) were probed using PROCESS , an add - on for SPSS [32] .
Data analysis was conduct using SPSS 17.0 ( IBM , Chicago , IL , USA ) and Mplus 6.1 .
Data from the surveys were double - entered and analyzed using SPSS ver. 19 ( IBM , Armonk , NY , USA ) .
Statistical analyzes were performed using the STATA version 13 application ( StataCorp , College Station , Texas , USA ) and the thematic maps were constructed using the QGIS software version 2.12.3 ( OSGeo , Beaverton , OR , USA ) .
Tests on initiatorship and overtaking were run with PASW Statistics 18 ( SPSS Inc . , Chicago , IL , 2009 ) , the other tests were run using R software ( R Development Core Team , Vienna , Austria , R 2.11.1 ) .
Data analysis was performed using the SPSS 15.0 PC package ( SPSS Inc . , Chicago , IL ) , with statistical significance set at P < 0.05 .
Random effects meta - regressions were also performed in Stata using the package metareg [44] .
Statistical analyses were conducted using SAS software , version 9.3 [ PROC GENMOD , with options REPEATED , CORR = IND or AR , and DIST = NORMAL ; SAS Institute , Inc . , Cary , NC ] .
Analyses were made using Mplus 7.1 software [28] and IBM SPSS Statistics 22.0 .
Hierarchical linear regression models were used as the main statistical method , using the user - written runmlwin command in Stata to fit multilevel models in the MLwiN software package v. 2.27 [37] .
The model was implemented in Matlab 2015b ( The Mathworks , Natick , MA ) and is available in S1 Code and at famulare.github .io / cessationStability .
SPSS software ( version 18.0 ) and R software ( version 3.4.3 ) were used for statistical analysis .
All data were entered into the IBM Statistical Package for the Social Sciences ( SPSS ) 18 .
Significance was set at the p = 0.05 level , and analyses were conducted using IBM SPSS Statistics Version 24 .
The statistical analysis was performed using the Statistical Package for Social Sciences ( SPSS for windows , version 19.0 ; Chicago , Illinois , USA ) .
All preprocessing , time - frequency SPM analyses , and ERP analyses were performed using SPM 8 ( http://www.fil.ion.ucl.ac.uk/spm ) implemented in MATLAB R 2012b ( MathWorks ) .
Reliability analysis of the data and univariate analyses were performed using SPSS version 16.0 ( SPSS Inc . , Chicago , IL , USA ) for Windows , and the SEM was produced using LISREL 8.5 .
All descriptive statistics , ANCOVA , and multiple regression analyses were conducted using SPSS 19.0 ( IBM , Armonk , New York ) .
As preference for future living arrangement was a non - ordered categorical variable , a multinomial regression model was performed using SPSS Version 20.0 ( IBM SPSS , Armonk , NY , USA ) to estimate the associations between various attributes and preferences for future living arrangements .
Interviews were transcribed and then manually coded using Microsoft Word and Excel .
Stata version 12.0 SE was used for all analyses .
All analyses were conducted in STATA , release 10.1 ( Statacorp . , College Station , TX , USA ) .
All analyses were done using IBM SPSS Statistics 20 ( IBM Corp 2011 ) [35] .
Statistical analyses were performed using Stata 11.0 ( StataCorp , College Station , Texas , USA ) .
SPSS version 22.0 ( SPSS , Inc . ) , R [42] and EpiTools [43] programs were used to explore our datasets .
All statistical analyses aside from the CFA were performed using STATA version 11 [28] .
Analyses were performed in SPSS version 18.0 ( Version 18.0 . Chicago : SPSS Inc . ) .
The statistical analysis was performed using the Statistical Package for Social Sciences ( SPSS for Windows , version 19.0 ; IBM Corp , Armonk , New York , USA ) .
The statistical analysis was done with Stata 14.1 ( Stata Corp LP , College station , Texas ) .
We used the Statistical Package for Social Sciences ( IBM SPSS v. 24.0.0.0 ) for all analyses .
All the processing , analyses , and machine learning were conducted using the MATLAB software package ( version R 2009a and R 2015a , Mathworks Inc . , Natick , MA , USA ) .
Analysis was performed using Stata version 13 and REALCOM - IMPUTE software [38] .
Statistical analyses were conducted using SPSS 23 ( IBM Corp . , Armonk , N.Y . , USA ) .
Indirect effects within samples ( mediation ) were analyzed using Hayes ’ s ( [53] ; version 2.16 ) SPSS macro PROCESS for model 4 , and indirect effect across samples ( moderated mediation ) were analyzed using Hayes ’ s SPSS macro PROCESS for model 8 .
Analyses were performed using Stata , version 13 ( StataCorp LP , TX ) .
Survey data from both SA and NZ ( n = 4,842 ) were downloaded from SurveyMonkey [49] and initial data screening was conducted in Microsoft Excel .
Statistical analyses were conducted using Statistical Package for the Social Sciences Version 20.0 ( SPSS 20.0 ) and Analysis of Moment Structures Version 20.0 ( AMOS 20.0 ) .
Non - parametric tests were applied using SPSS 17.0 ( SPSS Inc . ) , with the level of significance set at alpha = 0.05 .
All analyses were undertaken using Stata 15.0 ( StataCorp , College Station TX ) .
Images were preprocessed and analyzed using SPM 5 ( Wellcome Department of Cognitive Neurology , London , UK ) , implemented in MatLab 7.2 ( MathWorks ™ ) .
All analyses were conducted using Stata version 11 ( StataCorp , College Station , Texas ) and Excel version 2007 ( Microsoft Corporation , Redmond , Washington ) .
The multiple mediation analysis was performed using PROCESS for SPSS [29] .
For questions for which answers could be “ yes , ” “ I don ' t know ” or “ no , ” ( e.g. , “ Did any of the field sites have a code of conduct ? ” ) , KH and JR conservatively bifurcated responses into “ yes ” and “ not yes . ” Chi - square , t - test , and regression models were constructed in JMP 9.0 ( SAS , Inc ) .
Demographic , clinical , and laboratory data from the electronic medical record and study forms were de - identified , entered into an Excel spreadsheet , and exported into Stata v 14 software ( StataCorp , 2011 , College Station , Texas ) for analysis .
BCa confidence intervals were calculated using the statistical software SAS 9 and the % BOOT and % BOOTCI macros ( http://support.sas.com/kb/24/982.html ) .
SPSS version 19.0 ( SPSS Inc . , Chicago , Ill . , USA ) was used for statistical data analysis .
Statistical analysis was performed using SPSS version 19.0 ( SPSS Inc . , Illinois , USA ) and the significance level was set at P < 0.05 .
Conventional statistical analysis was performed on the mean whole brain SampEn and H values of each subject in both groups using the Statistical Package for Social Sciences ( SPSS 18.0 ; Chicago , IL , USA ) software .
All statistical comparisons were performed within GraphPad Prism 5 ( GraphPad Software , Inc . , La Jolla , CA ) .
Tracking was performed using Ctrax [67] including the provided Matlab toolboxes for subsequent correction and analysis of tracking data .
The survey forms were scanned using an optical character recognizing ( OCR ) machine and data were analyzed using STATA 10.1 for Windows ( Stata Corp , College Station , TX , USA ) software .
The results of E - β - ocimene influence on honey bee behavioural development were analysed with a two - ways ANOVA ( years and treatments ) followed by Fisher post - hoc test ( STATVIEW 5.0 , SAS Institute , Cary , NC ) .
Statistical analyses were performed using SAS 9.3 ( SAS Institute INC . Cary , NC , USA ) , R software ( http://www.r-project.org ) , and a web - based PABAK - OS calculator ( http://www.singlecaseresearch.org/calculators/pabak-os ) .
Data were pre - processed and analysed using SPM 8 ( Wellcome Department of Cognitive Neurology , London UK ) ( http://www.fil.ion.ucl.ac.uk/spm ) running on MATLAB 2007b ( Mathworks Inc . , Natick , MA ) .
For the pre - processing and statistical analyses , the statistical parametric mapping software package ( SPM 5 , Wellcome Department of Cognitive Neurology , London ; www.fil.ion.ucl.ac.uk/spm ) was used and implemented in Matlab ( Mathworks , Inc . , Natick , MA , USA release 14 ) .
Statistical analyses were performed using Stata software , version 13 ( StataCorp , College Station , TX , US ) .
Manual annotations of social / sexual interactions and wheel running activity were done manually using the Caltech Behavior Annotator program , a software tool created in MATLAB designed to facilitate the rapid manual annotation of video sequences .
For both approaches we used the GLIMMIX procedure in SAS University Edition Software ( SAS Institute , Cary , NC ) .
Data was analyzed using Microsoft Excel and Statistical Package for Social Sciences ( SPSS ) version 16 .
The data were analyzed with MIXED procedure in the IBM SPSS Statistics software , version 21 ( IBM Corporation , Armonk , New York , USA ) .
All analyses were performed using SAS / STAT ™ software version 9.1 ( SAS Institute Inc . , Cary , NC ) , Statistical Package for the Social Sciences ™ for Windows ™ ( SPSS ™ version 14.1 , SPSS Inc . , Chicago , IL ) , and RevMan version 4.1 ( Cochrane Collaboration , Oxford , UK ) .
Data are weighted to control for the survey design and random intercept models run in Stata 13 [30] .
IBM SPSS Statistics , version 22.0 for Windows [64] was used for the statistical analyses .
All data were analyzed using IBM SPSS Statistics 20 ( SPSS Inc , Chicago , IL , 2011 ) .
Facial stimuli were presented to the subjects in 4 different blocks using MATLAB 7.0 ™ ( Mathworks Inc . , Sherborn , USA ) .
Results were computed using SPSS ver. 15 ( SPSS Inc , Illinois , USA ) , employing the ‘ Complex Samples ’ procedure required when using probability weights .
All data analysis was performed using IBM SPSS Statistics 18.0 .
Stata version 13.1 ( Stata Corp LP , College Station , Texas ) was used to estimate the analysis models .
All statistical tests were conducted in Stata 11 ( Stata Corp . , College Station , TX [41] ) .
We conducted all statistical analyses in Stata version 13.1 ( StataCorp , Texas , USA ) .
All analyses were conducted in Stata v. 12 ( StataCorp , TX , USA ) .
All the statistical analyses were conducted using IBM SPSS Statistics , version 20.0 .
DLMs were implemented using the dlnm package version 2.2.6 in R Studio ( Vienna , Austria ) and other analyses were performed in SAS ( v 9.4 , SAS Institute Inc . , Cary , NC ) .
Post - hoc pairwise comparisons between patrilines were conducted using Tukey ’ s HSD function in R version 3.0.1 [43] .
The collected data were analyzed in IBM SPSS for Windows - version 19 .
The following preprocessing procedures were performed using Statistical Parametric Mapping ( SPM 8 ) software ( Wellcome Department of Imaging Neuroscience ; London , UK ) implemented in MATLAB R 2009b ( MathWorks ; Natick , MA , USA ) for whole brain analysis : correction for head motion , adjustment of acquisition timing across slices , spatial normalization using the MNI template , and smoothing using a Gaussian kernel with a full width at a half - maximum of 5 mm .
Statistical analyses were performed using SPSS ( version 17.0 ; SPSS Japan Inc . , Tokyo , Japan ) .
Analyses were conducted using STATA Version 13 for Windows ( College Station , TX , USA ) .
Statistical analyses were performed using SPSS ™ version 18.0 ( Statistical Package for the Social Sciences ) .
The experimental routine was programmed using the Psychtoolbox - 3 [56] for Matlab 2014a ( Mathworks , Natick , MA ) .
Using the SPSS 18.0 software package ( IBM , Armonk , NY , USA ) , we employed one repeated - measures Analysis of Variance Analysis test ( ANOVA ) to check the effect of provocation .
All meta - analyses and statistical analyses in the pooled individual - level data were performed using Stata SE 11.0 ( Stata Corporation , College Station , Texas , USA ) .
The resampling procedures were conducted in Microsoft Excel 2010 using VBA code written by FAC ( Appendix S2 ) .
Regression models were estimated using IBM SPSS Version 22 .
The data were entered into an Excel database ( Excel Version 2013 , Microsoft , Redmont , Washington , USA ) and checked for errors which might have occurred during data entry .
Analyses were conducted using SPSS version 24 for Mac ( IBM SPSS Statistics for Windows , Version 23 .
All statistical analyses were conducted using SPSS Statistics 22 ( Dynelytics , Zurich , Switzerland ) .
Behavioral data were analyzed with SPSS / PASW 18 .
The completed questionnaires were coded and entered into EPI info version 3.5.3 statistical software and then exported to SPSS windows version 20 program for analysis .
Statistical analyses were performed using STATA version 11 ( StataCorp , College Station , TX ) .
All the analyses were performed using Stata 12 ™ ( Stata Corporation , College Station , TX ) and accounted for the complex sampling design and the data weighting so that the estimates are representative of the entire population of HIV - infected individuals followed at hospitals in France .
All analyses were performed using STATA 11.0 ( Statacorp , College Station , TX ) .
The SAS version 9.1.3 program package was used for all analyses ( SAS Institute , Inc . , Cary , NC , USA ) .
All analyses were conducted using the statistical software SPSS , Version 20 ( IBM Statistics ) .
Statistical analyses were conducted using the Statistical Package for the Social Science ( SPSS ) version 19.0 and a p - value of less than 0.05 was used to define statistical significance .
We loaded the transcripts into MAXQDA 11 which is a software tool used to analyze qualitative data [88] .
All statistical analyses were conducted using the computer program SPSS ( version 18.0 , SPSS , Inc . , Chicago , IL ) .
Data were analysed using SPSS Statistics 21 for Macintosh ( SPSS , IBM Inc . ) .
Data were analyzed using SPSS for Windows ( version 20.0 , 2012 , SPSS Inc . , Chicago , IL , US ) .
The experiment was programmed with the Experiment Builder Software ( version 1.10.1630 ; SR Research Ltd . , Ottawa , Canada ) and data processing and analysis was performed using the open - source statistical programming language R ( www.r-project.org ) and Matlab ™ R 2011b ( Mathworks , Inc . , Natick , MA , USA ) .
Simultaneous relationships among variables were tested using path analysis with IBM SPSS AMOS 22 software .
SPSS software , version 18.0 ( SPSS Inc . , Chicago , IL , USA ) was used for all analyses .
The 2006 - survey data were double entered and cleaned in Epi Info 6.04 ( CDC , Atlanta ; WHO , Geneva 1996 ) , and analyzed with STATA 9.0 software ( Stata Corp . , College Station , TX ) .
All statistical analyses of this study were performed using SAS version 9.3 and STATA IC / SE 14 .
All statistical analyses were conducted using the statistical software package Stata 13 ( STATA Corp , College Station , TX ) , and the p - value < 0.05 was considered as statistically significant when performing hypothesis tests .
Analysis were conducted using SPSS vs . 20.0 ( IBM Corp . , released 2011 , Armonk , NY ) and GraphPad Prism 7.0 software ( GraphPad Software , Inc . , San Diego , CA ) .
These analyses were performed using IBM SPSS v. 21 .
We used SPSS 20.0 for Windows ( SPSS Inc . , Chicago , IL ) for all analyses .
The data were analyzed using statistical software STATA version 13 and statistical package for social science ( SPSS ) version 22 .
All analyses were conducted using Stata V. 11 [16] .
SPSS 16.0 for Windows was used for data analysis ; p values of < 0.05 were taken as statistically significant .
We analyzed data using JMP ™ v. 8.0 ( SAS Institute Inc . , Cary , NC ) , comparing males and females for all variables using a t - test and considered results significant if α ≤ 0.05 [47] .
Genetic correlations with antipsychotics dosage , PANSS score , and altruistic tendency were analyzed using the linear - by - linear association test , Mann - Whitney U test and linear regression tests in the SPSS v 11.5 package ( SPSS , Chicago , IL , USA ) .
Analyses were done using SPSS 20 and SAS 9.4 , the cut - off for statistical significance was set at p < .05 .
All statistical analyses were carried out with SPSS 19.0 software for Windows .
We analyzed data in Stata version 14.0 ( StataCorp , College Station , Texas ) .
The analysis was performed using SPSS 17 ( PASW ) for Windows ( SPSS Inc . , Chicago , Illinois , USA ) .
Logistic regression was conducted using SAS 9.3 software ( SAS PROC SURVEYLOGISTICS ; SAS Institute , Cary , NC ) .
All analyses were conducted using Stata version 13 [41] .
Data were analyzed using Statistical Parametric Mapping 5 ( SPM 5 , Wellcome Department of Cognitive Neurology , London , UK ) software implemented in Matlab 7.8 ( Mathworks , Sherborn , MA , USA ) .
We performed all analyses using the Statistical Package for the Social Sciences version 18.0 ( SPSS Inc , Chicago , IL , USA ) .
To investigate the relationship between the physiological correlates ( HRV and IS ) and ER as well as parental psychopathology , partial correlation tests were calculated ( alpha = .05 , two - tailed ) with the SPSS software package ( version 20 , IBM , Chicago , IL , USA ) .
The Statistical Package for the Social Sciences ( SPSS ) Version 19.0 ( SPSS , Chicago , IL ) and XLSTAT ( Addinsoft SARL , Germany ) were used to conduct analyses .
Based on two - sample Wilcoxon rank - sum test with a two - tail test α of 5 % with 80 % power , it was estimated that at least 96 mother - child pairs would be required to detect a 20 % difference in the mean duration of ABF between the intervention and control groups ( POWER procedure , SAS Version 9.3 , SAS Institute , Cary , NC , USA ) .
All the statistical analyses were performed using SAS ( Version 9.3 , SAS Institute , Cary , NC , USA ) .
Data were cleaned in Access and then analyzed using SAS 9.3 ( SAS Institute Inc . ) .
The tool is built in MS Excel 2010 and consists of two modules : i ) HPV vaccination , and ii ) cervical cancer screening and treatment [15] .
All of the statistical analyses were conducted using SPSS 17.0 ( SPSS Inc . , Chicago , IL , USA ) .
Data analysis was performed in Stata , version 15.0 , and R , version 3.4.0 .
As the name already indicates , the random effects model has the limiting assumption that the unobserved heterogeneity is randomly distributed , and therefore independent from the regressors ( we have used the XTNBREG , FE command in Stata 8 to estimate our fixed effects model , and the XTNBREG , RE command in Stata 8 to estimate our random effects model ) .
Data was entered and analyzed using Statistical Package for Social Sciences version - 16 ( SPSS IBM , New York , NY , USA ) .
The data were entered into Epi Info version 6 and transferred into SPSS version 17 ( SPSS Inc , Chicago , IL , USA ) .
Data was analyzed using SPSS 19.0 ( SPSS , Inc . , Chicago , IL , USA ) .
All statistical analyses used Stata v 14 ( StataCorp 2015 ) or R v 3.2.2 ( www.R-project.org ) .
Eighty - seven sequences were aligned using ClustalW and Geneious Pro 6.0 ( Biomatters Ltd ) .
We used the Datamonkey server and the HyPhy software package ( Kosakovsky Pond et al . 2005 ; Delport et al . 2010 ) to test for purifying selection , positive selection , and episodic selection at the codon level and the branch level among the phylogenies we generated .
Target genes of miR - 497 - 5p were firstly predicted using microRNA ( http://www.microrna.org/microrna/home.do ) , TargetScan ( http://www.targetscan.org ) , and miRDB ( http://mirdb.org/ ) , and then , intersection analyzed by Venny ( version 2.1.0 ; http://bioinfogp.cnb.csic.es/tools/venny/index.html ) .
After that , PPI Network ( https://www.theppinetwork.com/ ) was used to analyze interactions among different proteins , MCODE APP ( http://apps.cytoscape.org/apps/mcode ) was used for functional clustering of the proteins .
Gene expression data of miR - 497 - 5p and polycomb repressive complex 1 - associated protein ( CBX 4 ) in cancer tissues and tumor - adjacent tissues of cervical cancer patients were downloaded from TCGA Research Network ( https://www.cancer.gov/tcga ) using the UCSC Xena platform ( https://xenabrowser.net/hub/ ) , and used to analyze the genes ’ expression relationship on Online software Xena .
Image lab v 3.0 software ( Bio - Rad , Hercules , CA , USA ) was used to acquire and analyze imaging signals .
The result was analyzed using ModFit software version 3.2 ( Verity Software House , Topsham , ME , USA ) .
The results were analyzed using SPSS 20.0 statistical software ( IBM , Armonk , NY , USA ) .
To investigate the mechanism by which miR - 497 - 5p regulates the growth of cervical cancer cells , we used microRNA , TargetScan and miRDB to predict the potential target genes of miR - 497 - 5p .
Statistical analysis was performed using the SPSS and Excel software , version 2010 for Mac .
The results were analyzed with SigmaStat ™ 3.1 for Windows ™ ( Systat Software Inc . , Richmond , CA ) .
The microscope was also equipped with a digital high - resolution camera ( ProgResTM C10 ; Jenoptik , Jena , Germany ) and a computer - driven motorized stage ( ProScanTM ™ H128 Series ; Prior Scientific Instruments , Cambridge , UK ) , connected to an image analysis computer program ( Image - Pro Plus 5.1 for Windows ( IPP ) ; Media Cybernetics , Silver Spring , MD ) with a microscope controller module ( Scope - Pro 5.0 for Windows ; Media Cybernetics , Silver Spring , MD ) .
Reconstructed images were further processed using image - editing software ( Adobe ™ Photoshop ™ CS ver. 8.0.1 ; Adobe Systems Inc . , San Jose , CA ) when needed to produce printouts .
These AOI were automatically counted , and data was exported and saved to a spreadsheet computer program ( Microsoft Office Excel 2003 ; Microsoft Corporation , Redmond , WA ) .
Finally , the data were represented as a filled contour plot using graphing software ( SigmaPlot 9.0 for Windows ; Systat Software , Inc . , Richmond , CA ) that constructs pseudocolored isodensity maps in a scale of 45 different steps ( each of 125 ) ranging from 0 to 5,625 cells / mm .
Statistical analysis of the differences between groups of retinas or groups of animals was conducted with non - parametric ANOVA tests using Satistix ™ V 1.0 for Windows ™ 95 ( Analytical Software , Tallahassee , FL ) software ; the Kruskal - Wallis test was used to compare more than two groups , and the Mann - Whitney test was used when comparing two groups only .
The Figure was generated using GraphPad Prism version 7.01 , GraphPad Software , La Jolla California USA , www.graphpad.com.
All data were analysed using SPSS statistics version 17.0.0 released Aug 23 . 2008 ( SPSS Inc , Chicago , USA ) .
Adapter removal was performed using the Trimmomatic utility v 32.0 ( [52] ) , with a stringency parameter of 7 , very short reads < 8 nt were excluded .
The alignment of raw reads was conducted by Bowtie 2 ( [53] ) in end - to - end mode .
Statistical analyses for incubation periods were performed using A Kruskal - Wallis test followed by Dunn ’ s multiple comparisons test using GraphPad Prism 7.0 for windows ( GraphPad Software , La Jolla California , USA ) .
The GLM procedure of Minitab software , version 16.1 ( Minitab Inc . , 2010 ) was used and with the following model of fixed factors and their interactions :
To rationalize the anti - cancer potential of FKB derivatives , the online web Prediction of Activity Spectra for Substances ( PASS ) server was used to predict the biological activity of potential FKB derivatives [49,50] .
All the graphics were rendered using MOE and Chimera [53] .
The resulting trajectories were analyzed using the CPPTRAJ module in AMBERTOOLS 16 [55,56] .
Data reduction and absorption correction were performed using the SAINT and SADABS programs [62] .
Photomicrographs were taken with an inverted Olympus IX - 81 microscope equipped with a CoolSnap HQ digital camera and the ImagePro + software ( version 5.0.1 ; Media Cybernetics ) .
The cycle numbers crossing an arbitrary threshold ( Ct ) were determined using MyIQ system software , version 1.0.410 ( BioRad , CA , U.S .A . ) .
Statistical analysis and visualization of data from microarray experiments was performed using the software package FlexArray version 1.6 developed and provided by Genome Quebec .
Finally , membranes were developed with enhanced chemiluminescence ( ECL ) western blotting substrate ( ThermoFischer Scientific ) , scanned using a LAS 4000 Biomolecular imager ( GE Healthcare ) and analysed with ImageQuant TL version 7.0 software ( GE Healthcare ) .
Sum projection of 2 Z - stacks separated 2 μ m from each other was done with the freeware ImageJ v 1.51 u by Wayne Rasband ( National Institutes of Health , Bethesda , MD , USA ) and images were next automatically quantified with the NIS - Elements Microscope Imaging Software ( Nikon ) .
Graphpad prism 7.01 software ( Graphad Software ) was used for statistical analysis .
As expected , the symmetric Pt ( IV ) complexes have logP values that decreased in the order 3 > 4 > 2 > 1 ( − 0.26 , − 1.65 , − 2.69 , and − 3.05 , respectively ; Table 3 ) in accordance with the decreasing order of lipophilicity of the coordinated axial ligands ( benzoate > chloride > acetate > hydroxide , as simulated by the specific software Alogps 2.1 ; www.vcclab.org ) .
The IVDDM and IVDGE of feedstuffs were compared using the MIXED procedure of SAS ( SAS v 9.2 , SAS Institute Inc . , Cary , NC , USA ) , where feedstuffs were treated as fixed factor and batch as random factor .
We generated multilevel logistic regression models with random intercepts to evaluate the impact of patients and trust factors on each dependent variable using MLWin V. 2.31 software ( Rasbash J , Charlton C , Browne W , et al . MLwiN , Version 2.31 . Centre for Multilevel Modelling , University of Bristol ) .
We used reweighted iterative least squares and penalised quasi - likelihood method with outputs fed into a Markov chain Monte - Carlo model with 10 000 iterations which resulted in convergence for all analyses ( Browne WJ . MCMC estimation in MLwiN v 2.31 . Centre for Multilevel Modelling , University of Bristol ) .
Dataset filtering and Lowess normalization were performed using J - Express ( Molmine , Hafrsfjord , Norway ) as described [16] .
Bioinformatic analyses were performed using R [17] , version 2.15 , and BioConductor [18] , release 2.10 .
Gene - set enrichment analyses were performed using gene set enrichment analysis GSEA v 5.0 [19] .
In detail , cluster analysis was performed with genes belonging to the ERBB 2 amplicon after performing median centering of the amplicon genes using Cluster 3.0 and TreeView softwares .
ECM 3 was identified using the Large Average Submatricies ( LAS ) biclustering method [25] ; compactness and separation of cluster partitions were evaluated using the Dunn index and silhouette width [26] ; connectedness of clusters was quantified using the connectivity measure [26] , as previously described [4] .
Images were obtained using a × 60 oil immersion lens ( 512 × 512 or 1024 × 1024 pixels ) and analyzed using Image - Pro Plus v. 7.0.1 ( MediaCybenetics , Rockville , MD , USA ) software .
The data were log ( 2 ) transformed and normalized using Partek Genomics Suite ( Partek Inc . , St . Louis , MO ) .
Data were analyzed using GraphPad Prism version 5.0 for Mac OS X .
Peak lists were generated using extract - msn as part of Bioworks 3.3.1 ( Thermo Scientific ) using the following parameters : minimum mass 300 ; maximum mass 5,000 ; grouping tolerance 0.01 Da ; intermediate scans 200 ; minimum group count 1 ; 10 peaks minimum and total ion current of 100 .
LC - MS / MS spectra were searched against the NCBI RefSeq database [46] in a target decoy fashion using MASCOT ( v 2.4 , Matrix Science , U.K . ) .
The functional networks of identified proteins was constructed using ClueGO v 1.7.1 [47] , a Cytoscape v 2.8.3 [48] plugin .
The protein - protein interaction networks were further separated into different clusters and biological significance of these clusters were depicted using clusterMaker v. 1.8 and BiNGO v. 2.44 cytoscape plugins , respectively .
Statistical analysis was performed with Prism 5 ( GraphPad ) and Microsoft Office Excel .
Immunoratio [16] , for example , is an open - source software based on ImageJ [17] , another open - source software available as either a stand - alone or Web application .
ImageJ [17] is a public domain , Java - based image - processing program developed at the National Institutes of Health .
R language [30] ( version 3.2.2 ; R Foundation , Vienna , Austria ) was used for statistical analysis and creation of several figures .
Receiver operating characteristic ( ROC ) and accuracy performance of V and Immunoratio were computed using the ROCR package [32] .
For computational fluid dynamics simulations ( CFD software 18.0 from Ansys , Canonsburg , USA ) three - dimensional models of the microfluidic system with the enclosed larva were created using computer - aided design ( CAD software from SolidWorks , Velizy - Villacoublay , France ) .
Leica .xlef files were converted in .lif files and the latter were loaded into Imaris 9.1.2 ( Bitplane , Zurich , Switzerland ) .
Imaris was used to visualize and process the 4D datasets and to create movies ( see Supplementary Movies [3-7] and [9,10] ) together with Fiji ( https://fiji.sc/ ) , Adobe Photoshop CC ( 19.1.8 ) , and Quicktime 7.6.3 Pro ( Apple , Cupertino , CA , USA ) .
Images were processed and assembled using Adobe Photoshop CC ( 19.1.8 ) and Illustrator CC ( 22.1 ) , respectively .
Graphs for calcium traces were created with Prism 8.2.1 ( GraphPad , La Jolla , CA , USA ) and Adobe Illustrator CC ( 22.1 ) .
Cluster analysis of cytokine transcripts was performed with Gene Cluster ( version 3.0 ) and visualized with Treeview ( version 1.1.6r 4 ) .
CIBERSORT analyses were performed on RNAseq data by using the analytical tool developed by Newman et al . ( http://cibersort.stanford.edu ) [30] .
Gene correlation analysis and feature correlation heatmaps were performed on the PIVOT platform , developed by the Kim Lab ( http://kim.bio.upenn.edu/software/pivot.shtml ) [65] .
Sample correlation analyses were performed on PIVOT [65] or on Cluster ( version 3.0 ) and visualized in TreeView ( http://jtreeview.sourceforge.net ) .
FACS data were analyzed with FlowJo 2 , version 1.1.0 .
The Statistical Analysis System for Windows , version 9.4 ( SAS Institute , Cary , NC , USA ) , was used for analysis .
FastQ files were processed according to the GATK Best Practices : Alignment using bwa - mem , marking of duplicate reads using Picard , base recalibration using GATK , quality metrics were assessed using Picard .
Furthermore , variants identified by MuTect 2 that did not pass the built - in filters were reintroduced if they were identified with high confidence using VarScan 2 [40] ( pileups generated using samtools [41] ) .
The MuPeXI webserver [43] was then used to extract 8 to 11 length peptides around missense mutations , indels and frameshift mutations from the somatic VCF files and all mutant peptides with a binding prediction to MHC below 2 % ( weak binders ) from NetMHCpan [44] were retained as neoantigens .
Genotyping , logR Ratio ( LRR ) and B - allele - fraction ( BAF ) were corrected and normalized using the Genotyping module from GenomeStudio 2.0 ( Illumina ) and all positions with cluster separation > 0.75 were exported ( 594k SNPs ) for further analysis .
The R package ASCAT [45] was used for segmentation of the genome but various tumor DNA purities together with high heterogeneity made it difficult to obtain reliable somatic copy number estimates .
SNVs and their trinucleotide context were subjected to mutational signature analysis using R packages SomaticSignatures [46] and MutationalPatterns [47] .
Missense mutations in genes related to DDR were analyzed for potentially damaging effects using Polyphen 2 [18] and MutationAssessor [19] .
Mutations identified as possibly damaging / probably damaging or medium / high in PolyPhen 2 and MutationAssessor , respectively , were considered damaging .
The R - packages , tximport [52] and edgeR [53] , were used to respectively summarize the expression at gene - level and normalize the data .
Samples were classified according to the six consensus classes of MIBC using the R - based consensus MIBC classification tool ( n = 121 ) [15] .
We investigated transcriptional regulatory networks consisting of transcription factors and associated induced / repressed target genes using R package RTN [54] .
Data were imported and normalized using the ChAMP R package [59] .
Cumulative survival analysis was performed using the Kaplan - Meier method , and the log - rank test was used to compare the curves ( R packages survminer and survival ) .
The strength of the association between iNOS ( rs 2297518 ) and eNOS ( rs 2070744 , rs 1799983 ) polymorphisms and the risk of gastric cancer were evaluated by calculating pooled ORs and their corresponding 95 % CIs by using RevMan 5.1 ( Copenhagen , Denmark ) and Stata 12.0 ( StataCorp LP , College Station , TX , USA ) .
Microsoft Kinect for Windows includes C language applications , Visual Basic , C # , and an interface Developer Toolkits .
Diffusion image preprocessing was done using FSL 4.1.4 ( www.fmrib.ox.ac.uk/fsl ) .
All registration steps were done using trilinear interpolation as implemented in FLIRT ( Jenkinson and Smith 2001 ; FSL 4.1.4 ) .
Diffusion image analyses were performed using FSL 4.1.4 ( www.fmrib.ox.ac.uk/fsl ) .
Data management and analysis were performed using SPSS 15.0 for Windows .
The clean reads were aligned to the pig reference genome ( Sscrofa 11.1 ) using TopHat 2 [11] .
Differential expression genes between the infected and control groups were identified with the DESeq of R package [13] .
Peaking calling of the ChIP samples was conducted by comparison with the reads of input using MACS 2 [21] , with the significance level of p < 0.005 .
The statistical analyses were performed using IBM SPSS version 19.0 ( IBM Corp . , Armonk , NY , USA ) .
From each PCLS , triplicates of 30 μ m thick 3D stacks were recorded randomly and analyzed using IMARIS 7.4.0 software ( Bitplane Scientific Software , Zurich , Switzerland ) , as described previously [7] .
After addition of each concentration of Mch ( 10 to 10 M ) , pictures were recorded in 5 s intervals for 3 min with a stereo microscope ( Discovery V 8 ; Zeiss , Jena , Germany ) controlled by the Axio Vision 4.8.2 . software program ( Zeiss , Jena , Germany ) .
Mann - Whitney tests were performed for statistical analyses using GraphPad 4.03 ( GraphPad , San Diego , CA ) .
The data were tabulated using the IBM SPSS Statistics V 21 program , with the significance level set at p < 0.05 .
Table 1 shows that due to its implementation in the R environment , glmnet has a much heftier memory requirement than our C + + implementation and could not load the 1 million SNP dataset .
Execution times were similar between glmnet and gpu - lasso , where gpu - lasso was slightly faster .
MAP was calculated using the values of systolic blood pressure ( SBP ) and diastolic blood pressure ( DBP ) by the Iox 2.9.5.73 software ( Emka Technologies , Paris , France ) .
Heart rate and RR intervals were obtained using Iox 2.9.5.73 software ( Emka Technologies , Paris , France ) , with an acquisition frequency of 500 Hz .
Data were evaluated using GraphPad Prism Software , version 6 ( GraphPad Software Inc . , San Diego , CA , USA ) and presented as mean values with SEM .
Statistical analysis was performed using the SPSS software package ( version 17.0 , SPSS Inc . , Armonk , NY , USA ) and GraphPad Prism 5 ( GraphPad Software , La Jolla , CA , USA ) .
To further validate this result , we analyzed RNA - Seq data ( from TCGA : The Cancer Genome Atlas ) of lncRNAs of NSCLC were from TANRIC [23] ( http://ibl.mdanderson.org/tanric/_design/basic/index.html ) .
The synergistic activity of sorafenib and perifosine used in combination on the viability of 5637 and T24 BC cells was determined by the isobologram and CI methods ( CompuSin Software , ComboSyn , Inc . Paramus , NJ 2007 ) .
Molecular docking analysis was performed on Linux Red Hat Pentium 4 - based platform using Autodock Vina [57] and InsightII software ( Release 2005 , Accelrys Ltd . , Cambridge , U.K ) .
PyMOL software ( DeLano Scientific LLC , San Carlos , CA , 2009 - 10 ) was used to render all the output from InsightII and to calculate the distances of hydrogen bonds as measured between the hydrogen and its assumed binding partner .
