title: LUMPY: a probabilistic framework for structural variant discovery.
abstract: Comprehensive discovery of structural variation (SV) from whole genome sequencing data requires multiple detection signals including read-pair, split-read, read-depth and prior knowledge. Owing to technical challenges, extant SV discovery algorithms either use one signal in isolation, or at best use two sequentially. We present LUMPY, a novel SV discovery framework that naturally integrates multiple SV signals jointly across multiple samples. We show that LUMPY yields improved sensitivity, especially when SV signal is reduced owing to either low coverage data or low intra-sample variant allele frequency. We also report a set of 4,564 validated breakpoints from the NA12878 human genome. https://github.com/arq5x/lumpy-sv.
authors: Ryan M
authors: RM
authors: Layer
authors: Colby
authors: C
authors: Chiang
authors: Aaron R
authors: AR
authors: Quinlan
authors: Ira M
authors: IM
authors: Hall
mesh_terms: D056905:Chromosome Breakpoints; D004252:DNA Mutational Analysis; D005787:Gene Frequency; D014644:Genetic Variation; D015894:Genome, Human; D006720:Homozygote; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D009369:Neoplasms / Q000235:genetics; D012372:ROC Curve