A genome-wide approach for detecting novel insertion-deletion variants of mid-range size

Li C. Xia, Sukolsak Sakshuwong, Erik S. Hopmans, John M. Bell, Susan M. Grimes, David O. Siegmund, Hanlee P. Ji, Nancy R. Zhang

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)e126
JournalNucleic acids research
Volume44
Issue number15
DOIs
StatePublished - Sep 6 2016

ASJC Scopus subject areas

  • Genetics

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