sanjaynagi / rna-seq-pop

Snakemake workflow for Illumina RNA-sequencing experiments - extract population genomic signals from RNA-Seq data
https://sanjaynagi.github.io/rna-seq-pop/
MIT License
18 stars 7 forks source link
ancestry differential-expression genomic-surveillance karyotype population-genetics population-genomics rna-seq selection snakemake snakemake-workflow transcriptomics variant-calling workflow
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Documentation: https://sanjaynagi.github.io/rna-seq-pop/

Walkthrough: https://www.youtube.com/watch?v=5QQe7DLHO4M

RNA-Seq-Pop is a computational pipeline to analyse Illumina RNA-Sequencing data of any organism. As well as performing standard transcriptomic analyses, such as differential expression, RNA-Seq-Pop also calls and analyses genetic polymorphisms, extracting population genomic signals. The workflow can perform the following analyses of illumina paired-end RNA-Sequencing data:

The workflow is generalised, and will function with any Illumina single or paired-end RNA-sequencing. However, certain modules, such as the ancestry and karyotyping, are only appropriate for An. gambiae s.l. These can be activated in the configuration file (config.yaml). The workflow works with pooled samples, diploid, or haploid individuals.

If you have any feedback on how the workflow may be improved, please do get in touch, or feel free to fork the github repo and create a pull request for any additional features you would like to implement. If you are using the workflow and would like to give feedback or troubleshoot, consider joining the discord server here, otherwise email or log an issue on github.

Authors

Citation

Sanjay C Nagi, Ambrose Oruni, David Weetman, Martin J Donnelly (2022). RNA-Seq-Pop: Exploiting the sequence in RNA-Seq - a Snakemake workflow reveals patterns of insecticide resistance in the malaria vector Anopheles gambiae. Molecular Ecology Resources; doi: https://onlinelibrary.wiley.com/doi/10.1111/1755-0998.13759

If you use this workflow in a paper, please give credits to the author by citing the manuscript and its DOI - https://onlinelibrary.wiley.com/doi/10.1111/1755-0998.13759

Usage

Please see the documentation for instructions on how to run and contribute to RNA-Seq-Pop.