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PMID: 17115056 Published · ppublish English Journal Article Research Support, N.I.H., Extramural

Automating resequencing-based detection of insertion-deletion polymorphisms.

Nature genetics ·Vol. 38 ·No. 12 ·2006-12-00 ·Pages 1457-62

Bhangale TR, Stephens M, Nickerson DA

Abstract

Structural and insertion-deletion (indel) variants have received considerable recent attention, partly because of their phenotypic consequences. Among these variants, the most common are small indels ( approximately 1-30 bp). Identifying and genotyping indels using sequence traces obtained from diploid samples requires extensive manual review, which makes large-scale studies inconvenient. We report a new algorithm, implemented in available software (PolyPhred version 6.0), to help automate detection and genotyping of indels from sequence traces. The algorithm identifies heterozygous individuals, which permits the discovery of low-frequency indels. It finds 80% of all indel polymorphisms with almost no false positives and finds 97% with a false discovery rate of 10%. Additionally, genotyping accuracy exceeds 99%, and it correctly infers indel length in 96% of the cases. Using this approach, we identify indels in the HapMap ENCODE regions, providing the first report of these polymorphisms in this data set.

MeSH Terms
Algorithms DNA Transposable Elements Genetic Techniques Heterozygote Humans Mutation Polymorphism, Genetic Polymorphism, Single Nucleotide Sequence Analysis, DNA Sequence Deletion
Chemicals
DNA Transposable Elements
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Bhangale Tushar R
Department of Bioengineering, University of Washington, Seattle, Washington 98195, USA.
Stephens Matthew
Nickerson Deborah A
Article Info
Journal
Nature genetics
Abbr.
Nat Genet
ISSN
1061-4036
Published
2006-12-00
Epub
2006-00-19
Pages
1457-62
Language
English
Region
United States
NLM ID
9216904
Subset
IM
Grants
NHGRI NIH HHS · HG/LM02585 · United States
NHLBI NIH HHS · HL66682 · United States
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