Literature DB >> 34146471

A community challenge to evaluate RNA-seq, fusion detection, and isoform quantification methods for cancer discovery.

Allison Creason1, David Haan2, Kristen Dang3, Kami E Chiotti1, Matthew Inkman4, Andrew Lamb3, Thomas Yu3, Yin Hu3, Thea C Norman3, Alex Buchanan1, Marijke J van Baren2, Ryan Spangler1, M Rick Rollins1, Paul T Spellman1, Dmitri Rozanov1, Jin Zhang4, Christopher A Maher4, Cristian Caloian5, John D Watson5, Sebastian Uhrig6, Brian J Haas7, Miten Jain2, Mark Akeson2, Mehmet Eren Ahsen8, Gustavo Stolovitzky9, Justin Guinney3, Paul C Boutros10, Joshua M Stuart2, Kyle Ellrott11.   

Abstract

The accurate identification and quantitation of RNA isoforms present in the cancer transcriptome is key for analyses ranging from the inference of the impacts of somatic variants to pathway analysis to biomarker development and subtype discovery. The ICGC-TCGA DREAM Somatic Mutation Calling in RNA (SMC-RNA) challenge was a crowd-sourced effort to benchmark methods for RNA isoform quantification and fusion detection from bulk cancer RNA sequencing (RNA-seq) data. It concluded in 2018 with a comparison of 77 fusion detection entries and 65 isoform quantification entries on 51 synthetic tumors and 32 cell lines with spiked-in fusion constructs. We report the entries used to build this benchmark, the leaderboard results, and the experimental features associated with the accurate prediction of RNA species. This challenge required submissions to be in the form of containerized workflows, meaning each of the entries described is easily reusable through CWL and Docker containers at https://github.com/SMC-RNA-challenge. A record of this paper's transparent peer review process is included in the supplemental information.
Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cancer; Cloud compute; DREAM Challenge; RNA fusion; RNA-seq; benchmark; crowd-sourced; evaluation; isoform quantification

Mesh:

Substances:

Year:  2021        PMID: 34146471      PMCID: PMC8376800          DOI: 10.1016/j.cels.2021.05.021

Source DB:  PubMed          Journal:  Cell Syst        ISSN: 2405-4712            Impact factor:   11.091


  41 in total

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5.  Apparent non-canonical trans-splicing is generated by reverse transcriptase in vitro.

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Journal:  PLoS One       Date:  2010-08-18       Impact factor: 3.240

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Authors:  Rob Patro; Geet Duggal; Michael I Love; Rafael A Irizarry; Carl Kingsford
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8.  Evaluation of variable selection methods for random forests and omics data sets.

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10.  FusionHub: A unified web platform for annotation and visualization of gene fusion events in human cancer.

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Journal:  PLoS One       Date:  2018-05-01       Impact factor: 3.240

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Journal:  Front Microbiol       Date:  2022-03-09       Impact factor: 5.640

4.  Experimentally Deduced Criteria for Detection of Clinically Relevant Fusion 3' Oncogenes from FFPE Bulk RNA Sequencing Data.

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5.  Target isoforms are an overlooked challenge and opportunity in chimeric antigen receptor cell therapy.

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6.  In silico validation of RNA-Seq results can identify gene fusions with oncogenic potential in glioblastoma.

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7.  mRNA Capture Sequencing and RT-qPCR for the Detection of Pathognomonic, Novel, and Secondary Fusion Transcripts in FFPE Tissue: A Sarcoma Showcase.

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Journal:  Int J Mol Sci       Date:  2022-09-20       Impact factor: 6.208

  7 in total

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