Dissemin is shutting down on January 1st, 2025

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Nature Research, Nature Methods, 12(10), p. 1185-1191, 2013

DOI: 10.1038/nmeth.2722

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Systematic evaluation of spliced alignment programs for RNA-seq data.

Journal article published in 2013 by ItalyJeltje van Baren, Daniel R. Zerbino, Michael Zhang, Cole Trapnell, Barbara Wold, Armand Valsesia, Thomas D. Wu, David Weese, Simon White, Xiaowo Wang, Jie Wu, Chenghai Xue, Thomas Wu, Giorgio Valle, Nicola Vitulo and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

: High-throughput RNA sequencing is an increasingly accessible method for studying gene structure and activity on a genome-wide scale. A critical step in RNA-seq data analysis is the alignment of partial transcript reads to a reference genome sequence. To assess the performance of current mapping software, we invited developers of RNA-seq aligners to process four large human and mouse RNA-seq data sets. In total, we compared 26 mapping protocols based on 11 programs and pipelines and found major performance differences between methods on numerous benchmarks, including alignment yield, basewise accuracy, mismatch and gap placement, exon junction discovery and suitability of alignments for transcript reconstruction. We observed concordant results on real and simulated RNA-seq data, confirming the relevance of the metrics employed. Future developments in RNA-seq alignment methods would benefit from improved placement of multimapped reads, balanced utilization of existing gene annotation and a reduced false discovery rate for splice junctions.