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...

Descripción completa

Detalles Bibliográficos
Autores principales: Baccarella, Alyssa, Williams, Claire R., Parrish, Jay Z., Kim, Charles C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234607/
https://www.ncbi.nlm.nih.gov/pubmed/30428853
http://dx.doi.org/10.1186/s12859-018-2445-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234607/
https://www.ncbi.nlm.nih.gov/pubmed/30428853
http://dx.doi.org/10.1186/s12859-018-2445-2

Ejemplares similares