PT  - JOURNAL ARTICLE
AU  - Páll Melsted
AU  - Shannon Hateley
AU  - Isaac Charles Joseph
AU  - Harold Pimentel
AU  - Nicolas Bray
AU  - Lior Pachter
TI  - Fusion detection and quantification by pseudoalignment
AID  - 10.1101/166322
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 166322
4099  - http://biorxiv.org/content/early/2017/07/20/166322.short
4100  - http://biorxiv.org/content/early/2017/07/20/166322.full
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