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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...
Enregistré dans:
| Publié dans: | BMC Bioinformatics |
|---|---|
| Auteurs principaux: | , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
BioMed Central
2018
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| 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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