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Integrating Bacterial ChIP‐seq and RNA‐seq Data With SnakeChunks
Author(s) -
Rioualen Claire,
CharbonnierKhamvongsa Lucie,
ColladoVides Julio,
Helden Jacques
Publication year - 2019
Publication title -
current protocols in bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.535
H-Index - 57
eISSN - 1934-340X
pISSN - 1934-3396
DOI - 10.1002/cpbi.72
Subject(s) - workflow , computer science , automation , rna seq , modular design , data science , database , data mining , computational biology , gene , biology , transcriptome , engineering , genetics , mechanical engineering , gene expression , operating system
Next‐generation sequencing (NGS) is becoming a routine approach in most domains of the life sciences. To ensure reproducibility of results, there is a crucial need to improve the automation of NGS data processing and enable forthcoming studies relying on big datasets. Although user‐friendly interfaces now exist, there remains a strong need for accessible solutions that allow experimental biologists to analyze and explore their results in an autonomous and flexible way. The protocols here describe a modular system that enable a user to compose and fine‐tune workflows based on SnakeChunks, a library of rules for the Snakemake workflow engine. They are illustrated using a study combining ChIP‐seq and RNA‐seq to identify target genes of the global transcription factor FNR in Escherichia coli , which has the advantage that results can be compared with the most up‐to‐date collection of existing knowledge about transcriptional regulation in this model organism, extracted from the RegulonDB database. © 2019 by John Wiley & Sons, Inc.

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