ABRA: improved coding indel detection via assembly-based realignment
Author(s) -
Lisle E. Mose,
Matthew D. Wilkerson,
D. Neil Hayes,
Charles M. Perou,
Joel S. Parker
Publication year - 2014
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btu376
Subject(s) - indel , computer science , indel mutation , java , coding (social sciences) , data mining , computational biology , genetics , biology , genotype , gene , single nucleotide polymorphism , programming language , statistics , mathematics
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.
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