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

By Thomas D. Wu, Serban Nacu. Bioinform., 2010

1,989 citations recorded by the source corpus.

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

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ace57ab6080e9b7538c7d519d848ca4cbd32c546

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Citations in the corpus

Metabolic Induction of Trained Immunity through the Mevalonate Pathway. (2018, neutral): “…Zhang et al., 2008 https://github.com/taoliu/MACS/ Bedtools Quinlan and Hall, 2010 http://bedtools.readthedocs.io/en/latest/ GSNAP Wu and Nacu, 2010 http://research-pub.gene.com/gmap/ Caret https://cran.r-project.org/web/packages/caret/ index.html HOMER Heinz et al., 2010…”
Next-generation transcriptome assembly (2011, methodology): “…steps: aligning the RNA-Seq reads to a reference genome using a splice-aware aligner such as TopHat 45 , SpliceMap 46 , MapSplice 47 , or GSNAP 48 ( Box 1 ); clustering overlapping reads from each locus to build a graph representing all possible isoforms, and traversing the graph to resolve…”
A survey of sequence alignment algorithms for next-generation sequencing (2010, background): “Most aligners capable of bisulfite alignments [24, 57] do the following.”
Software for Computing and Annotating Genomic Ranges (2013, methodology): “Each of these variant assessment tools makes use of infrastructure derived from GSNAP [11] with key results materialized as GRanges instances.”
Predicting Genes in Single Genomes with AUGUSTUS (2018, methodology): “Short read RNA-seq data (e.g., Illumina or short 454 reads) can be aligned individually to the target genome to obtain spliced read information [e.g., using STAR (Dobin et al., 2013), GSNAP (Wu & Nacu, 2010) or Tophat2 (Daehwan et al., 2013)].”
Complexity of the Alternative Splicing Landscape in Plants[C][W][OPEN] (2013, methodology): “Theseed-extendmethodstartsbysplitting the reads followedby their alignment andseedextension (Genomic Short-Read Nucleotide Alignment Program and QPALMA).”