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SCORE: Smart Consensus Of RNA Expression-a consensus tool for detecting differentially expressed genes in bacteria
- Source :
- Bioinformatics (Oxford, England). 37(3)
- Publication Year :
- 2020
-
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. Availability and implementation https://github.com/SiWolf/SCORE. Supplementary information Supplementary data are available at Bioinformatics online.
- Subjects :
- Statistics and Probability
Consensus
Computer science
Computational biology
Biochemistry
Transcriptome
03 medical and health sciences
0302 clinical medicine
Gene expression
Molecular Biology
030304 developmental biology
0303 health sciences
biology
Bacteria
Sequence Analysis, RNA
Gene Expression Regulation, Bacterial
biology.organism_classification
Computer Science Applications
Computational Mathematics
Differentially expressed genes
Rna expression
Computational Theory and Mathematics
030217 neurology & neurosurgery
Software
Subjects
Details
- ISSN :
- 13674811
- Volume :
- 37
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Bioinformatics (Oxford, England)
- Accession number :
- edsair.doi.dedup.....5d411b36b881e19b2628747f9c2122ba