A genome-wide approach for detecting novel insertion-deletion variants of mid-range size
Author(s) -
Xiaoling Zhang,
Sukolsak Sakshuwong,
Erik Hopmans,
John Bell,
Susan M. Grimes,
David Siegmund,
Hanlee P. Ji,
Nancy Zhang
Publication year - 2016
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkw481
Subject(s) - biology , genome , computational biology , in silico , genetics , dna sequencing , range (aeronautics) , genomics , deep sequencing , k mer , dna , gene , materials science , composite material
We present SWAN, a statistical framework for robust detection of genomic structural variants in next-generation sequencing data and an analysis of mid-range size insertion and deletions (<10 Kb) for whole genome analysis and DNA mixtures. To identify these mid-range size events, SWAN collectively uses information from read-pair, read-depth and one end mapped reads through statistical likelihoods based on Poisson field models. SWAN also uses soft-clip/split read remapping to supplement the likelihood analysis and determine variant boundaries. The accuracy of SWAN is demonstrated by in silico spike-ins and by identification of known variants in the NA12878 genome. We used SWAN to identify a series of novel set of mid-range insertion/deletion detection that were confirmed by targeted deep re-sequencing. An R package implementation of SWAN is open source and freely available.
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