OncoThreads: visualization of large-scale longitudinal cancer molecular data.
Journal
Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944
Informations de publication
Date de publication:
12 07 2021
12 07 2021
Historique:
entrez:
12
7
2021
pubmed:
13
7
2021
medline:
16
7
2021
Statut:
ppublish
Résumé
Molecular profiling of patient tumors and liquid biopsies over time with next-generation sequencing technologies and new immuno-profile assays are becoming part of standard research and clinical practice. With the wealth of new longitudinal data, there is a critical need for visualizations for cancer researchers to explore and interpret temporal patterns not just in a single patient but across cohorts. To address this need we developed OncoThreads, a tool for the visualization of longitudinal clinical and cancer genomics and other molecular data in patient cohorts. The tool visualizes patient cohorts as temporal heatmaps and Sankey diagrams that support the interactive exploration and ranking of a wide range of clinical and molecular features. This allows analysts to discover temporal patterns in longitudinal data, such as the impact of mutations on response to a treatment, for example, emergence of resistant clones. We demonstrate the functionality of OncoThreads using a cohort of 23 glioma patients sampled at 2-4 timepoints. Freely available at http://oncothreads.gehlenborglab.org. Implemented in Java Script using the cBioPortal web API as a backend. Supplementary data are available at Bioinformatics online.
Identifiants
pubmed: 34252935
pii: 6319672
doi: 10.1093/bioinformatics/btab289
pmc: PMC8275328
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
i59-i66Subventions
Organisme : NHGRI NIH HHS
ID : R00 HG007583
Pays : United States
Organisme : Drug Discovery & Translational Research Program
Organisme : NIH HHS
ID : R00 HG007583
Pays : United States
Organisme : Novartis to the Dana-Farber Cancer Institute
Informations de copyright
© The Author(s) 2021. Published by Oxford University Press.
Références
Comput Graph Forum. 2016 Jun;35(3):491-500
pubmed: 27942091
Nat Methods. 2014 Sep;11(9):884-885
pubmed: 25166867
IEEE Trans Vis Comput Graph. 2005 Jul-Aug;11(4):443-56
pubmed: 16138554
Nat Biotechnol. 2020 Jun;38(6):675-678
pubmed: 32444850
BMC Bioinformatics. 2017 Sep 12;18(1):406
pubmed: 28899361
Cancer Discov. 2012 May;2(5):401-4
pubmed: 22588877
IEEE Trans Vis Comput Graph. 2011 Dec;17(12):2301-9
pubmed: 22034350
IEEE Trans Vis Comput Graph. 2014 Dec;20(12):2023-32
pubmed: 26356916
Ann Oncol. 2017 Dec 1;28(12):3076-3082
pubmed: 28950321
Sci Signal. 2013 Apr 02;6(269):pl1
pubmed: 23550210
IEEE Trans Vis Comput Graph. 2014 Dec;20(12):1783-92
pubmed: 26356892
Comput Graph Forum. 2019 Jun;38(3):781-805
pubmed: 31768085
Nature. 2010 Apr 15;464(7291):993-8
pubmed: 20393554
IEEE Trans Vis Comput Graph. 2013 Dec;19(12):2277-86
pubmed: 24051794
Cell. 2020 Apr 16;181(2):236-249
pubmed: 32302568
BMC Genomics. 2016 Nov 7;17(1):880
pubmed: 27821060
Contemp Oncol (Pozn). 2015;19(1A):A68-77
pubmed: 25691825
AMIA Annu Symp Proc. 2012;2012:716-25
pubmed: 23304345
IEEE Trans Vis Comput Graph. 2013 Dec;19(12):2227-36
pubmed: 24051789
Clin Cancer Res. 2006 Jan 15;12(2):328-31
pubmed: 16428468
Science. 2014 Jan 10;343(6167):189-193
pubmed: 24336570
Comput Graph Forum. 2012 Jun;31(33):1175-1184
pubmed: 27942089