Benchmarking of RNA-sequencing analysis workflows using whole-transcriptome RT-qPCR expression data.

ABSTRACT: RNA-sequencing has become the gold standard for whole-transcriptome gene expression quantification. Multiple algorithms have been developed to derive gene counts from sequencing reads. While a number of benchmarking studies have been conducted, the question remains how individual methods perform at accurately quantifying gene expression levels from RNA-sequencing reads. We performed an independent benchmarking study using RNA-sequencing data from the well established MAQCA and MAQCB reference samples. RNA-sequencing reads were processed using five workflows (Tophat-HTSeq, Tophat-Cufflinks, STAR-HTSeq, Kallisto and Salmon) and resulting gene expression measurements were compared to expression data generated by wet-lab validated qPCR assays for all protein coding genes. All methods showed hi

SUBMITTER: Everaert C 

PROVIDER: S-EPMC5431503 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature