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Empirical assessment of the impact of sample number and read depth on RNA-Seq analysis workflow performance

BACKGROUND: RNA-Sequencing analysis methods are rapidly evolving, and the tool choice for each step of one common workflow, differential expression analysis, which includes read alignment, expression modeling, and differentially expressed gene identification, has a dramatic impact on performance cha...

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Détails bibliographiques
Publié dans:BMC Bioinformatics
Auteurs principaux: Baccarella, Alyssa, Williams, Claire R., Parrish, Jay Z., Kim, Charles C.
Format: Artigo
Langue:Inglês
Publié: BioMed Central 2018
Sujets:
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC6234607/
https://ncbi.nlm.nih.gov/pubmed/30428853
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-018-2445-2
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