| Literature DB >> 30786165 |
Claire Rioualen1,2, Lucie Charbonnier-Khamvongsa1, Julio Collado-Vides2,3, Jacques van Helden1,4.
Abstract
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.Entities:
Keywords: ChIP-seq; Escherichia coli K-12; FAIR Guiding Principles; RNA-seq; reproducible science; workflow
Mesh:
Year: 2019 PMID: 30786165 PMCID: PMC7302399 DOI: 10.1002/cpbi.72
Source DB: PubMed Journal: Curr Protoc Bioinformatics ISSN: 1934-3396