Evidence map›Paper›PMID 22689759›Full record

ArticleBioinformatics (Oxford, England)2012

Dissect: detection and characterization of novel structural alterations in transcribed sequences.

Deniz Yorukoglu, Faraz Hach, Lucas Swanson, Colin C Collins, Inanc Birol, S Cenk Sahinalp

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Structural variation in the sequencing era.Nature reviews. Genetics · 2020
    Review
  2. Article
  3. Article
  4. Article
  5. Identifying fusion transcripts using next generation sequencing.Wiley interdisciplinary reviews. RNA · 2016
    Review
  6. Review
  7. Article
  8. Updating RNA-Seq analyses after re-annotation.Bioinformatics (Oxford, England) · 2013
    Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Deniz YorukogluSchool of Computing Science, Simon Fraser University, Burnaby, V5A 1S6 BC, Canada. denizy@mit.edu
Faraz Hach
Lucas Swanson
Colin C Collins
Inanc Birol
S Cenk Sahinalp

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationComputational identification of genomic structural variants via high-throughput sequencing is an important problem for which a number of highly sophisticated solutions have been recently developed. With the advent of high-throughput transcriptome sequencing (RNA-Seq), the problem of identifying structural alterations in the transcriptome is now attracting significant attention. In this article, we introduce two novel algorithmic formulations for identifying transcriptomic structural variants through aligning transcripts to the reference genome under the consideration of such variation. The first formulation is based on a nucleotide-level alignment model; a second, potentially faster formulation is based on chaining fragments shared between each transcript and the reference genome. Based on these formulations, we introduce a novel transcriptome-to-genome alignment tool, Dissect (DIScovery of Structural Alteration Event Containing Transcripts), which can identify and characterize transcriptomic events such as duplications, inversions, rearrangements and fusions. Dissect is suitable for whole transcriptome structural variation discovery problems involving sufficiently long reads or accurately assembled contigs.

resultsWe tested Dissect on simulated transcripts altered via structural events, as well as assembled RNA-Seq contigs from human prostate cancer cell line C4-2. Our results indicate that Dissect has high sensitivity and specificity in identifying structural alteration events in simulated transcripts as well as uncovering novel structural alterations in cancer transcriptomes. AVAILABILITY: Dissect is available for public use at: http://dissect-trans.sourceforge.net.

Indexed as

AlgorithmsTranscriptomeCell Line, TumorGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansMaleModels, TheoreticalProstatic NeoplasmsRNASequence AlignmentSequence Analysis, RNARNA

Identifiers

PMID22689759
PMCPMC3371846

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.