Abstract
Summary: RNA-sequencing (RNA-Seq) is the current method of choice for studying bacterial transcriptomes. To date, many computational pipelines have been developed to predict differentially expressed genes from RNA-Seq data, but no gold-standard has been widely accepted. We present the Snakemake-based tool Smart Consensus Of RNA Expression (SCORE) which uses a consensus approach founded on a selection of well-established tools for differential gene expression analysis. This allows SCORE to increase the overall prediction accuracy and to merge varying results into a single, human-readable output. SCORE performs all steps for the analysis of bacterial RNA-Seq data, from read preprocessing to the overrepresentation analysis of significantly associated ontologies. Development of consensus approaches like SCORE will help to streamline future RNA-Seq workflows and will fundamentally contribute to the creation of new gold-standards for the analysis of these types of data.
Cite
CITATION STYLE
Wolf, S. A., Epping, L., Andreotti, S., Reinert, K., & Semmler, T. (2021). SCORE: Smart Consensus Of RNA Expression - a consensus tool for detecting differentially expressed genes in bacteria. Bioinformatics, 37(3), 426–428. https://doi.org/10.1093/bioinformatics/btaa681
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