Fast and SNP-tolerant detection of complex variants and splicing in short reads

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ID: 291062
2010
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Abstract
Next-generation sequencing captures sequence differences in reads relative to a reference genome or transcriptome, including splicing events and complex variants involving multiple mismatches and long indels. We present computational methods for fast detection of complex variants and splicing in short reads, based on a successively constrained search process of merging and filtering position lists from a genomic index. Our methods are implemented in GSNAP (Genomic Short-read Nucleotide Alignment Program), which can align both single- and paired-end reads as short as 14 nt and of arbitrarily long length. It can detect short- and long-distance splicing, including interchromosomal splicing, in individual reads, using probabilistic models or a database of known splice sites. Our program also permits SNP-tolerant alignment to a reference space of all possible combinations of major and minor alleles, and can align reads from bisulfite-treated DNA for the study of methylation state.In comparison testing, GSNAP has speeds comparable to existing programs, especially in reads of > or=70 nt and is fastest in detecting complex variants with four or more mismatches or insertions of 1-9 nt and deletions of 1-30 nt. Although SNP tolerance does not increase alignment yield substantially, it affects alignment results in 7-8% of transcriptional reads, typically by revealing alternate genomic mappings for a read. Simulations of bisulfite-converted DNA show a decrease in identifying genomic positions uniquely in 6% of 36 nt reads and 3% of 70 nt reads.Source code in C and utility programs in Perl are freely available for download as part of the GMAP package at http://share.gene.com/gmap.
Reference Key
openalex_W2096441981 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Thomas D. Wu, Şerban Nacu
Journal BMC Bioinformatics
Year 2010
DOI
10.1093/bioinformatics/btq057
URL
https://academic.oup.com/bioinformatics/article-pdf/26/7/873/48855440/bioinformatics_26_7_873.pdf
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