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OmicsView:通过交互式可视化分析进行组学数据分析。

OmicsView: Omics data analysis through interactive visual analytics.

作者信息

Casey Fergal, Negi Soumya, Zhu Jing, Sun Yu H, Zavodszky Maria, Cheng Derrick, Lin Dongdong, John Sally, Penny Michelle A, Sexton David, Zhang Baohong

机构信息

Translational Biology, Research Development, Biogen, Inc., Cambridge, MA 02142, USA.

BioInfoRx, Inc., 510 Charmany Dr, Suite 275A, Madison, WI 53719, USA.

出版信息

Comput Struct Biotechnol J. 2022 Mar 10;20:1277-1285. doi: 10.1016/j.csbj.2022.02.022. eCollection 2022.

Abstract

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 ( or ). 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.

摘要

随着二代测序(NGS)技术的进步,对多种疾病的人体组织进行转录谱分析正变得越来越常规化,这导致了数PB的数据被存入公共数据库。对于几乎没有计算专业知识的实验台科学家来说,需要能够访问和挖掘这些数据,以了解疾病病理学、识别可靠的疾病生物标志物以及干预措施的效果。为此,我们发布了一个名为OmicsView的用于表达数据的开源分析和可视化平台,网址为http://omicsview.org。该平台预先加载了来自许多疾病领域和正常组织的数千个样本,包括基因型组织表达(GTEx)数据库,所有样本均通过统一的流程进行处理。我们通过一项克罗恩病数据挖掘实践展示了该平台的强大功能和易用性,在该实践中,我们能够快速揭示疾病病理学特征,并识别出疾病和治疗反应的强生物标志物。

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