RT Journal Article
SR Electronic
T1 Fusion detection and quantification by pseudoalignment
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 166322
DO 10.1101/166322
A1 Páll Melsted
A1 Shannon Hateley
A1 Isaac Charles Joseph
A1 Harold Pimentel
A1 Nicolas Bray
A1 Lior Pachter
YR 2017
UL http://biorxiv.org/content/early/2017/07/20/166322.abstract
AB RNA sequencing in cancer cells is a powerful technique to detect chromosomal rearrangements, allowing for de novo discovery of actively expressed fusion genes. Here we focus on the problem of detecting gene fusions from raw sequencing data, assembling the reads to define fusion transcripts and their associated breakpoints, and quantifying their abundances. Building on the pseudoalignment idea that simplifies and accelerates transcript quantification, we introduce a novel approach to fusion detection based on inspecting paired reads that cannot be pseudoaligned due to conflicting matches. The method and software, called pizzly, filters false positives, assembles new transcripts from the fusion reads, and reports candidate fusions. With pizzly, fusion detection from raw RNA-Seq reads can be performed in a matter of minutes, making the program suitable for the analysis of large cancer gene expression databases and for clinical use. pizzly is available at https://github.com/pmelsted/pizzly