Simulation-based comprehensive benchmarking of RNA-seq aligners
Benchmarking on synthetic data reveals differences between common RNA-seq alignment software tools, particularly for complex genomic regions. 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 pipeli...
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Veröffentlicht in: | Nature methods 2017-02, Vol.14 (2), p.135-139 |
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Sprache: | eng |
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Zusammenfassung: | Benchmarking on synthetic data reveals differences between common RNA-seq alignment software tools, particularly for complex genomic regions.
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. |
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ISSN: | 1548-7091 1548-7105 |
DOI: | 10.1038/nmeth.4106 |