Published October 12, 2023 | Version v1
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Statistics to prioritize rare variants in family-based sequencing studies with disease subtypes

  • 1. Simon Fraser University and EMMES Canada
  • 2. Simon Fraser University
  • 3. BC Cancer and Simon Fraser University
  • 4. Université Laval and Centre de recherche CERVO

Description

Code and Data for Analyses in Nieuwoudt et al.

This repository contains the code and data for the analyses that appear in the preprint Statistics to prioritize rare variants in family-based sequencing studies with disease subtypes by Christina Nieuwoudt, Fabiha Binte Farooq, Angela Brooks-Wilson, Alexandre Bureau and Jinko Graham. The preprint can be found at the DOI https://doi.org/10.1101/2023.09.28.560053.

Directory structure

The files for the example data analysis from Section 3.1 of the preprint are in the directory Example of this repository. The files for the rank-only analysis in Appendix A of the preprint are in the directory RankOnly of this repository. See the README files in the respective directories for further details.

R packages

We do our analyses in R, and require the R packages SimRVSequences and RVMethods, available from GitHub. The package versions used in the analyses are archived at https://github.com/simrvprojects/SimRVSequences/releases/tag/v0.1 and https://github.com/simrvprojects/RVMethods/releases/tag/v0.1, respectively. Instructions for installing these packages are given in the Example/example.Rmd and RankOnly/rankonly.Rmd R Markdown files. Version numbers of other R packages installed as dependencies are shown in the following sessionInfo() output:

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base    

other attached packages:
[1] RVMethods_0.1.0      gRain_1.3.14         gRbase_1.9.0       
[4] SimRVSequences_0.2.4

loaded via a namespace (and not attached):
 [1] Matrix_1.5-4        dplyr_1.1.3         compiler_4.3.0    
 [4] BiocManager_1.30.22 tidyselect_1.2.0    Rcpp_1.0.11       
 [7] stringr_1.5.0       tidyr_1.3.0         Rgraphviz_2.43.0  
[10] lattice_0.21-8      SimRVPedigree_0.4.4 R6_2.5.1           
[13] plyr_1.8.8          intervals_0.15.3    generics_0.1.3    
[16] igraph_1.5.1        RBGL_1.75.0         knitr_1.43        
[19] backports_1.4.1     BiocGenerics_0.45.3 graph_1.77.2      
[22] tibble_3.2.1        pillar_1.9.0        rlang_1.1.1       
[25] utf8_1.2.3          broom_1.0.5         stringi_1.7.12    
[28] xfun_0.40           quadprog_1.5-8      cli_3.6.1         
[31] magrittr_2.0.3      grid_4.3.0          kinship2_1.9.6    
[34] lifecycle_1.0.3     vctrs_0.6.3         glue_1.6.2        
[37] stats4_4.3.0        fansi_1.0.4         reshape2_1.4.4    
[40] purrr_1.0.2         tools_4.3.0         pkgconfig_2.0.3 

Funding acknowledgement

•          Natural Sciences and Engineering Research Council of Canada RGPIN-04296-2018

•          Canadian Statistical Sciences Institute (CANSSI) Collaborative Research Team Project # 08

•          Canadian Institutes for Health Research MOP-130311

Notes

Funding acknowledgement • Natural Sciences and Engineering Research Council of Canada RGPIN-04296-2018 • Canadian Statistical Sciences Institute (CANSSI) Collaborative Research Team Project # 08 • Canadian Institutes for Health Research MOP-130311

Files

Example.zip

Files (3.3 MB)

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md5:130e98c93597d0eae7f61036c6439a53
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md5:c4481773b4f34675987c5d9865dafee9
2.5 MB Preview Download
md5:8373d0141c28e7f4e9db415398cc7e6c
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Additional details

Related works

Cites
Preprint: 10.1101/2023.09.28.560053 (DOI)