OmicsView: Omics data analysis through interactive visual analytics

被引:1
|
作者
Casey, Fergal [1 ]
Negi, Soumya [1 ]
Zhu, Jing [1 ]
Sun, Yu H. [1 ]
Zavodszky, Maria [1 ]
Cheng, Derrick [2 ]
Lin, Dongdong [1 ]
John, Sally [1 ]
Penny, Michelle A. [1 ]
Sexton, David [1 ]
Zhang, Baohong [1 ]
机构
[1] Biogen Inc, Translat Biol, Res Dev, Cambridge, MA 02142 USA
[2] BioInfoRx Inc, 510 Charmany Dr,Suite 275A, Madison, WI 53719 USA
关键词
Expression profiling; Expression databases; Visual analytics; Meta-analysis; RNAseq; GENE SET ENRICHMENT; DISEASE; CANCER; PLATFORM;
D O I
10.1016/j.csbj.2022.02.022
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
With advances in NGS technologies, transcriptional profiling of human tissue across many diseases is becoming more routine, leading to the generation of petabytes of data deposited in public repositories. There is a need for bench scientists with little computational expertise to be able to access and mine this data to understand disease pathology, identify robust biomarkers of disease and the effect of interventions (in vivo or in vitro). To this end we release an open source analytics and visualization platform for expression data called OmicsView, http://omicsview.org.This platform comes preloaded with 1000 s of samples across many disease areas and normal tissue, including the GTEx database, all processed with a harmonized pipeline. We demonstrate the power and ease-of-use of the platform by means of a Crohn's disease data mining exercise where we can quickly uncover disease pathology and identify strong biomarkers of disease and response to treatment.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:1277 / 1285
页数:9
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