SQUID: Transcriptomic structural variation detection from RNA-seq

Cong Ma, Mingfu Shao, Carl Kingsford

Research output: Contribution to journalArticle

2 Citations (Scopus)

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

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transcriptomics
RNA
gene fusion
gene
Gene Fusion
Genes
genes
neoplasms
Neoplasms
tumor
detection
cancer
sampling
simulation

All Science Journal Classification (ASJC) codes

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

Cite this

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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.",
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SQUID : Transcriptomic structural variation detection from RNA-seq. / Ma, Cong; Shao, Mingfu; Kingsford, Carl.

In: Genome biology, Vol. 19, No. 1, 52, 12.04.2018.

Research output: Contribution to journalArticle

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AU - Shao, Mingfu

AU - Kingsford, Carl

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AB - 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.

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