Published September 2, 2024 | Version v1.2
Dataset Open

Metagenome quality metrics and taxonomical annotation visualization through the integration of MAGFlow and BIgMAG (Sup. Material)

Creators

  • 1. ROR icon University of Fribourg
  • 2. Swiss Institute of Bioinformatics

Description

Dataset encompassing:

  • The recovered MAGs by 6 different metagenomics pipelines (ATLAS, DATMA, MetaWRAP, MUFFIN, nf-core/mag and SnakeMAGs) using a mock community as input (SRR8359173 and SRR9328980), complemented with the output from MAGFlow (v1.0.0) using these MAGs as input for their quality assessment and taxonomical annotation. 
  • The MAGs produced by nf-core/mag using rice/rhizosphere sequenced libraries (PRJNA663614, PRJNA448773 and PRJNA645385) in either single assembly/single binning or co-assembly/co-binning mode, complemented with the output from MAGFlow (v1.0.0) using these MAGs as input for their quality assessment and taxonomical annotation.
  • Scripts, commands and configuration files to run the different pipelines (ATLAS, DATMA, MetaWRAP, MUFFIN, nf-core/mag and SnakeMAGs) and reproduce the experimental conditions.
  • Outputs, commands and scripts to run Metabinner and Semibin in their default configuration using the rice soil samples co-assembly, along with the MAGFlow (v1.1.0) output to compare these binners against MetaBAT2.

Files

Files (3.1 GB)

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md5:7c2ce1e29f90b4a78c19997d3e9014a1
9.1 kB Download
md5:02d45c82e696ebb7695725e382034a31
997.2 MB Download
md5:6fb4770ee9a319524db3961a921c86eb
1.1 GB Download
md5:d6406701b627e38ace550227b0c6776c
957.2 MB Download

Additional details

Related works

Is derived from
Software: 10.5281/zenodo.13628774 (DOI)
Is supplemented by
Software: 10.5281/zenodo.13628741 (DOI)

Dates

Available
2024-05-25
Release of version 1.0
Available
2024-08-26
Release of version 1.1
Available
2024-09-02
Release of version 1.2

References

  • Kieser, S., Brown, J., Zdobnov, E. M., Trajkovski, M., & McCue, L. A. (2020). ATLAS: A Snakemake workflow for assembly, annotation, and genomic binning of metagenome sequence data. BMC Bioinformatics, 21(1), 1–8.
  • Benavides, A., Sanchez, F., Alzate, J. F., & Cabarcas, F. (2020). DATMA: Distributed Automatic Metagenomic Assembly and annotation framework. PeerJ, 8:e9762.
  • Krakau, S., Straub, D., Gourlé, H., Gabernet, G., & Nahnsen, S. (2022). nf-core/mag: a best-practice pipeline for metagenome hybrid assembly and binning. NAR Genomics and Bioinformatics, 4(1).
  • Uritskiy, G. V., Diruggiero, J., & Taylor, J. (2018). MetaWRAP - A flexible pipeline for genome-resolved metagenomic data analysis. Microbiome, 6(1), 1–13.
  • van Damme, R., Hölzer, M., Viehweger, A., Müller, B., Bongcam-Rudloff, E., & Brandt, C. (2021). Metagenomics workflow for hybrid assembly, differential coverage binning, metatranscriptomics and pathway analysis (MUFFIN). PLOS Computational Biology, 17(2), 1–13.
  • Tadrent, N., Dedeine, F., Hervé, V., Dias, C., Júnior, S., & Mikaelyan, A. (2023). SnakeMAGs: a simple, efficient, flexible and scalable workflow to reconstruct prokaryotic genomes from metagenomes. F1000Research, 11, 1522.
  • Akinola, Saheed Adekunle, Ayansina Segun Ayangbenro, and Olubukola Oluranti Babalola. (2021). "Metagenomic Insight into the Community Structure of Maize-Rhizosphere Bacteria as Predicted by Different Environmental Factors and Their Functioning within Plant Proximity." Microorganisms 9(7):1419.
  • Portik, D. M., Brown, C. T., & Pierce-Ward, N. T. (2022). Evaluation of taxonomic classification and profiling methods for long-read shotgun metagenomic sequencing datasets. BMC Bioinformatics, 23(1), 1–39.
  • Li, Y., Tremblay, J., Bainard, L. D., Cade-Menun, B., & Hamel, C. (2020). Long-term effects of nitrogen and phosphorus fertilization on soil microbial community structure and function under continuous wheat production. Environmental Microbiology, 22(3), 1066–1088.
  • Fernández-Baca, C. P., Rivers, A. R., Kim, W., Iwata, R., McClung, A. M., Roberts, D. P., Reddy, V. R., & Barnaby, J. Y. (2021). Changes in rhizosphere soil microbial communities across plant developmental stages of high and low methane emitting rice genotypes. Soil Biology and Biochemistry, 156, 108233.
  • Pan, S., Zhao, X. M., & Coelho, L. P. (2023). SemiBin2: self-supervised contrastive learning leads to better MAGs for short- and long-read sequencing. Bioinformatics, 39(Supplement_1), i21–i29.
  • Wang, Z., Huang, P., You, R., Sun, F., & Zhu, S. (2023). MetaBinner: a high-performance and stand-alone ensemble binning method to recover individual genomes from complex microbial communities. Genome Biology, 24(1), 1–18.