SQUID: Transcriptomic structural variation detection from RNA-seq

Cong Ma, Mingfu Shao, Carl Kingsford

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

Transcripts are frequently modified by structural variations, which lead to fused transcripts of either multiple genes, known as a fusion gene, or a gene and a previously non-transcribed sequence. Detecting these modifications, called transcriptomic structural variations (TSVs), especially in cancer tumor sequencing, is an important and challenging computational problem. We introduce SQUID, a novel algorithm to predict both fusion-gene and non-fusion-gene TSVs accurately from RNA-seq alignments. SQUID unifies both concordant and discordant read alignments into one model and doubles the precision on simulation data compared to other approaches. Using SQUID, we identify novel non-fusion-gene TSVs on TCGA samples.

Original languageEnglish (US)
Article number52
JournalGenome biology
Volume19
Issue number1
DOIs
StatePublished - Apr 12 2018

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

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