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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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 CSHL labs > Dobin Lab CSHL Cancer Center Program > Cancer Genetics and Genomics Program |
| Depositing User: | Matt Covey |
| Date: | 23 April 2016 |
| Date Deposited: | 26 Apr 2016 15:07 |
| Last Modified: | 05 Nov 2020 21:36 |
| PMCID: | PMC4842274 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/32618 |
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