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Nat Methods. 2017 Feb;14(2):135-139. doi: 10.1038/nmeth.4106. Epub 2016 Dec 12.

Simulation-based comprehensive benchmarking of RNA-seq aligners.

Author information

1
Department of Information Engineering, University of Padova, Padua, Italy.
2
Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania, Philadelphia, Pennsylvania, USA.
3
Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
4
Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Abstract

Alignment is the first step in most RNA-seq analysis pipelines, and the accuracy of downstream analyses depends heavily on it. Unlike most steps in the pipeline, alignment is particularly amenable to benchmarking with simulated data. We performed a comprehensive benchmarking of 14 common splice-aware aligners for base, read, and exon junction-level accuracy and compared default with optimized parameters. We found that performance varied by genome complexity, and accuracy and popularity were poorly correlated. The most widely cited tool underperforms for most metrics, particularly when using default settings.

PMID:
27941783
PMCID:
PMC5792058
DOI:
10.1038/nmeth.4106
[Indexed for MEDLINE]
Free PMC Article

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