A genome-wide approach for detecting novel insertion-deletion variants of mid-range size.
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.
Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA Department of Statistics, the Wharton School, University of Pennsylvania, Philadelphia, PA 18014, USA.
Li C
LC
Xia
Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Sukolsak
S
Sakshuwong
Stanford Genome Technology Centre, Stanford University, Palo Alto, CA 94304, USA.
Erik S
ES
Hopmans
Stanford Genome Technology Centre, Stanford University, Palo Alto, CA 94304, USA.
John M
JM
Bell
Stanford Genome Technology Centre, Stanford University, Palo Alto, CA 94304, USA.
Susan M
SM
Grimes
Department of Statistics, Stanford University, Stanford, CA 94305, USA.
David O
DO
Siegmund
Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA Stanford Genome Technology Centre, Stanford University, Palo Alto, CA 94304, USA nzh@wharton.upenn.edu.
Hanlee P
HP
Ji
Department of Statistics, the Wharton School, University of Pennsylvania, Philadelphia, PA 18014, USA nzh@wharton.upenn.edu.
Nancy R
NR
Zhang
D000256:Adenoviridae / Q000235:genetics; D000465:Algorithms; D000818:Animals; D019985:Benchmarking; D003198:Computer Simulation; D004252:DNA Mutational Analysis / Q000379:methods*; D066264:Datasets as Topic; D016678:Genome / Q000235:genetics*; D023281:Genomics / Q000379:methods*; D054643:INDEL Mutation / Q000235:genetics*; D002679:Pan troglodytes / Q000821:virology; D016012:Poisson Distribution; D015203:Reproducibility of Results