ABRA: improved coding indel detection via assembly-based realignment

Variant detection from next-generation sequencing (NGS) data is an increasingly vital aspect of disease diagnosis, treatment and research. Commonly used NGS-variant analysis tools generally rely on accurately mapped short reads to identify somatic variants and germ-line genotypes. Existing NGS read...

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Bibliographic Details
Published in:Bioinformatics (Oxford, England) England), 2014-10, Vol.30 (19), p.2813-2815
Main Authors: Mose, Lisle E, Wilkerson, Matthew D, Hayes, D Neil, Perou, Charles M, Parker, Joel S
Format: Article
Language:English
Subjects:
Algorithms
Applications Notes
Computational Biology - methods
Gene Frequency
Genome, Human
Genotype
High-Throughput Nucleotide Sequencing
Humans
INDEL Mutation
Programming Languages
Sequence Alignment - methods
Sequence Analysis, DNA - methods
Software
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Summary:Variant detection from next-generation sequencing (NGS) data is an increasingly vital aspect of disease diagnosis, treatment and research. Commonly used NGS-variant analysis tools generally rely on accurately mapped short reads to identify somatic variants and germ-line genotypes. Existing NGS read mappers have difficulty accurately mapping short reads containing complex variation (i.e. more than a single base change), thus making identification of such variants difficult or impossible. Insertions and deletions (indels) in particular have been an area of great difficulty. Indels are frequent and can have substantial impact on function, which makes their detection all the more imperative. We present ABRA, an assembly-based realigner, which uses an efficient and flexible localized de novo assembly followed by global realignment to more accurately remap reads. This results in enhanced performance for indel detection as well as improved accuracy in variant allele frequency estimation. ABRA is implemented in a combination of Java and C/C++ and is freely available for download at https://github.com/mozack/abra.
ISSN:1367-4803
1367-4811
DOI:10.1093/bioinformatics/btu376