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Empirical assessment of analysis workflows for differential expression analysis of human samples using RNA-Seq.
Williams CR, Baccarella A, Parrish JZ, Kim CC. Williams CR, et al. BMC Bioinformatics. 2017 Jan 17;18(1):38. doi: 10.1186/s12859-016-1457-z. BMC Bioinformatics. 2017. PMID: 28095772 Free PMC article.
However, RNA-Seq analysis is still rapidly evolving, with a large number of tools available for each of the three major processing steps: read alignment, expression modeling, and identification of differentially expressed genes. ...Additionally, …
However, RNA-Seq analysis is still rapidly evolving, with a large number of tools available for each of the three major …
Empirical assessment of the impact of sample number and read depth on RNA-Seq analysis workflow performance.
Baccarella A, Williams CR, Parrish JZ, Kim CC. Baccarella A, et al. BMC Bioinformatics. 2018 Nov 14;19(1):423. doi: 10.1186/s12859-018-2445-2. BMC Bioinformatics. 2018. PMID: 30428853 Free PMC article.
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 …
BACKGROUND: RNA-Sequencing analysis methods are rapidly evolving, and the tool choice for each step of one common workflow
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