Fast and SNP-tolerant detection of complex variants and splicing in short reads
Open accessAbstract
Motivation: 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. Results: In comparison testing, GSNAP has speeds comparable to existing programs, especially in reads of ≥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. Availability: 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. Contact: twu@gene.com
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The polymorphism-aware alignment strategy is likely most effective for intraspecific studies of species with relatively low levels of polymorphism because the number of possible haplotypes increases exponentially with the number of polymorphic sites.
“This is a viable strategy for both model and non-model species, but will likely be most effective for intraspecific studies of species like humans with relatively low levels of polymorphism because the number of possible haplotypes increases exponentially with the number of polymorphic sites.”
From Sources of bias in measures of allele-specific expression derived from RNA-seq data aligned to a single reference genome (2013) · cites this paper as [21]
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Experimental — accuracy not yet measuredSeveral RNA-seq mappers are optimized for specific tasks: identifying SNPs or indels (GSNAP, PALMapper, MapSplice), detecting non-canonical splice junctions (STAR, MapSplice), ultra-fast mapping (GEM), or mapping long reads (STAR).
“Several other mappers exist that are optimized to identify SNPs or indels (GSNAP [202], PALMapper [203] MapSplice [204]), detect non-canonical splice junctions (STAR [15], MapSplice [204]), achieve ultra-fast mapping (GEM [205]) or map long-reads (STAR [15]).”
From A survey of best practices for RNA-seq data analysis (2016) · cites this paper as [202]
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- Authors
- Wu, T. D., & Nacu, S.
- Affiliations
- Genentech (US)
- Department of Bioinformatics, Genentech, Inc., 1 DNA Way, South San Francisco, CA, USA
- Corresponding author
- Wu, Thomas D.
- ORCID
- Wu, Thomas D.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-02-10
- Volume
- 26
- Issue
- 7
- Pages
- 873-881
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC2844994
- OpenAlex
- W2096441981
- Cited by
- 1,894
- References
- 28
- Citations by year
- 2026: 45 · 2025: 63 · 2024: 81 · 2023: 87 · 2022: 89 · 2021: 97 · 2020: 121 · 2019: 150 · 2018: 170 · 2017: 199 · 2016: 178 · 2015: 176 · 2014: 184 · 2013: 125 · 2012: 69
- FWCI
- 33.11
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
- Keywords
- short-read alignment, splicing detection, constrained search, splice sites, bisulfite sequencing, DNA methylation, paired-end reads, GMAP
- MeSH terms
- Base Sequence, DNA, Recombinant, RNA Splicing, Genetic Variation, Polymorphism, Single Nucleotide, Genomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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