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Detecting genomic indel variants with exact breakpoints in single- and paired-end sequencing data using SplazerS.
- Source :
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Bioinformatics (Oxford, England) [Bioinformatics] 2012 Mar 01; Vol. 28 (5), pp. 619-27. Date of Electronic Publication: 2012 Jan 11. - Publication Year :
- 2012
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Abstract
- Motivation: The reliable detection of genomic variation in resequencing data is still a major challenge, especially for variants larger than a few base pairs. Sequencing reads crossing boundaries of structural variation carry the potential for their identification, but are difficult to map.<br />Results: Here we present a method for 'split' read mapping, where prefix and suffix match of a read may be interrupted by a longer gap in the read-to-reference alignment. We use this method to accurately detect medium-sized insertions and long deletions with precise breakpoints in genomic resequencing data. Compared with alternative split mapping methods, SplazerS significantly improves sensitivity for detecting large indel events, especially in variant-rich regions. Our method is robust in the presence of sequencing errors as well as alignment errors due to genomic mutations/divergence, and can be used on reads of variable lengths. Our analysis shows that SplazerS is a versatile tool applicable to unanchored or single-end as well as anchored paired-end reads. In addition, application of SplazerS to targeted resequencing data led to the interesting discovery of a complete, possibly functional gene retrocopy variant.<br />Availability: SplazerS is available from http://www.seqan.de/projects/ splazers.<br />Supplementary Information: Supplementary data are available at Bioinformatics online.
- Subjects :
- Algorithms
Humans
Genomics methods
INDEL Mutation
Sequence Analysis, DNA
Subjects
Details
- Language :
- English
- ISSN :
- 1367-4811
- Volume :
- 28
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Bioinformatics (Oxford, England)
- Publication Type :
- Academic Journal
- Accession number :
- 22238266
- Full Text :
- https://doi.org/10.1093/bioinformatics/bts019