LUMPY: A probabilistic framework for structural variant discovery

TL;DR

LUMPY is a flexible probabilistic framework that improves structural variant discovery in human genomes by integrating multiple signals, enhancing sensitivity especially at low coverage and for small variants.

Contribution

It introduces a novel probabilistic approach capable of integrating various SV detection signals, outperforming existing methods in sensitivity.

Findings

Enhanced sensitivity by combining paired-end and split-read signals.

Effective detection of small structural variants.

Applicable to heterogeneous tumor genome studies.

Abstract

Comprehensive discovery of structural variation (SV) in human genomes from DNA sequencing requires the integration of multiple alignment signals including read-pair, split-read and read-depth. However, owing to inherent technical challenges, most existing SV discovery approaches utilize only one signal and consequently suffer from reduced sensitivity, especially at low sequence coverage and for smaller SVs. We present a novel and extremely flexible probabilistic SV discovery framework that is capable of integrating any number of SV detection signals including those generated from read alignments or prior evidence. We demonstrate improved sensitivity over extant methods by combining paired-end and split-read alignments and emphasize the utility of our framework for comprehensive studies of structural variation in heterogeneous tumor genomes. We further discuss the broader utility of this approach for probabilistic integration of diverse genomic interval datasets.