A benchmark for RNA-seq quantification pipelines

Teng, M., Love, M. I., Davis, C. A., Djebali, S., Dobin, A., Graveley, B. R., Li, S., Mason, C. E., Olson, S., Pervouchine, D., Sloan, C. A., Wei, X., Zhan, L., Irizarry, R. A. (April 2016) A benchmark for RNA-seq quantification pipelines. Genome Biol, 17 (1). p. 74. ISSN 1474-760X (Electronic)1474-7596 (Linking)

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URL: http://www.ncbi.nlm.nih.gov/pubmed/27107712
DOI: 10.1186/s13059-016-0940-1

Abstract

Obtaining RNA-seq measurements involves a complex data analytical process with a large number of competing algorithms as options. There is much debate about which of these methods provides the best approach. Unfortunately, it is currently difficult to evaluate their performance due in part to a lack of sensitive assessment metrics. We present a series of statistical summaries and plots to evaluate the performance in terms of specificity and sensitivity, available as a R/Bioconductor package ( http://bioconductor.org/packages/rnaseqcomp ). Using two independent datasets, we assessed seven competing pipelines. Performance was generally poor, with two methods clearly underperforming and RSEM slightly outperforming the rest.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > computational biology
bioinformatics > genomics and proteomics > computers > computer software
Investigative techniques and equipment > assays > RNA-seq
CSHL Authors:
Communities: CSHL labs > Gingeras lab
Depositing User: Matt Covey
Date: 23 April 2016
Date Deposited: 26 Apr 2016 15:07
Last Modified: 12 Oct 2016 14:37
PMCID: PMC4842274
Related URLs:
URI: http://repository.cshl.edu/id/eprint/32618

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