title: MetaSV: an accurate and integrative structural-variant caller for next generation sequencing.
abstract: Structural variations (SVs) are large genomic rearrangements that vary significantly in size, making them challenging to detect with the relatively short reads from next-generation sequencing (NGS). Different SV detection methods have been developed; however, each is limited to specific kinds of SVs with varying accuracy and resolution. Previous works have attempted to combine different methods, but they still suffer from poor accuracy particularly for insertions. We propose MetaSV, an integrated SV caller which leverages multiple orthogonal SV signals for high accuracy and resolution. MetaSV proceeds by merging SVs from multiple tools for all types of SVs. It also analyzes soft-clipped reads from alignment to detect insertions accurately since existing tools underestimate insertion SVs. Local assembly in combination with dynamic programming is used to improve breakpoint resolution. Paired-end and coverage information is used to predict SV genotypes. Using simulation and experimental data, we demonstrate the effectiveness of MetaSV across various SV types and sizes.
  
  
  METHODS
  Code in Python is at http://bioinform.github.io/metasv/.
  
  
  BACKGROUND
  rd@bina.com
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: Bina Technologies, Roche Sequencing, Redwood City, CA 94065, USA.
authors: Marghoob
authors: M
authors: Mohiyuddin
authors: Bina Technologies, Roche Sequencing, Redwood City, CA 94065, USA.
authors: John C
authors: JC
authors: Mu
authors: Bina Technologies, Roche Sequencing, Redwood City, CA 94065, USA.
authors: Jian
authors: J
authors: Li
authors: Bina Technologies, Roche Sequencing, Redwood City, CA 94065, USA.
authors: Narges
authors: N
authors: Bani Asadi
authors: Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
authors: Mark B
authors: MB
authors: Gerstein
authors: Department of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA.
authors: Alexej
authors: A
authors: Abyzov
authors: Department of Statistics, Stanford University, Stanford, CA 94035, USA and Department of Health Research and Policy, Stanford University, Stanford, CA 94035, USA.
authors: Wing H
authors: WH
authors: Wong
authors: Bina Technologies, Roche Sequencing, Redwood City, CA 94065, USA.
authors: Hugo Y K
authors: HY
authors: Lam
mesh_terms: D014644:Genetic Variation; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D016254:Mutagenesis, Insertional; D017384:Sequence Deletion; D012984:Software