Seq2science: an end-to-end workflow for functional genomics analysis.

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Reanalyzing publicly available data, and integrating it with new, project-specific data sets, can be invaluable. With current technologies, genomic experiments have become feasible for virtually any species of interest. However, using and integrating this data comes with its challenges, such as standardized and reproducible analysis. Seq2science is a multi-purpose workflow that covers preprocessing, quality control, visualization, and analysis of functional genomics sequencing data. It facilitates the downloading of sequencing data from all major databases, including NCBI SRA, EBI ENA, DDBJ, GSA, and ENCODE. Furthermore, it automates the retrieval of any genome assembly available from Ensembl, NCBI, and UCSC. It has been tested on a variety of species, and includes diverse workflows such as ATAC-, RNA-, and ChIP-seq. It consists of both generic as well as advanced steps, such as differential gene expression or peak accessibility analysis and differential motif analysis. Seq2science is built on the Snakemake workflow language and thus can be run on a range of computing infrastructures. It is available at https://github.com/vanheeringen-lab/seq2science.", "claims": [{"id": "claim-method", "statement": "Independent of the configured gene expression quantification approach, the workflow supports differential gene expression analysis with DESeq2 (Love, Huber & Anders, 2014) with batch effect correction to integrate (multiple) datasets, and can prepare an exon count table for downstream use with DEXSeq (Anders, Reyes & Huber, 2012).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38025697", "locator": "sections[8] \"RNA-seq\" paragraph 3", "quote": "Independent of the configured gene expression quantification approach, the workflow supports differential gene expression analysis with DESeq2 (Love, Huber & Anders, 2014) with batch effect correction to integrate (multiple) datasets, and can prepare an exon count table for downstream use with DEXSeq (Anders, Reyes & Huber, 2012)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The following information was supplied regarding data availability:The software is available via the environment manager Anaconda and the seq2science package on bioconda (https://www.nature.com/articles/s41592-018-0046-7) and can be installed with “mamba install -c bioconda seq2science”.The source code is available at GitHub and Zenodo:• https://github.com/vanheeringen-lab/seq2science• Maarten van der Sande, Siebren Frölich, Jos Smits, Tilman Schäfers, Rebecca Snabel, & Simon van Heeringen. (2023). seq2science (v1.2.0). Zenodo. https://doi.org/10.5281/zenodo.8361102The regularly updated documentation is available at: https://vanheeringen-lab.github.io/seq2science/.The data is available at Zenodo: Maarten van der Sande, & Siebren Frölich. (2023). Seq2science manuscript supplementary data. 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