Abstract

A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.

With the increasing obtainability of multi-OMICs data comes the need for easy to use data analysis tools. Here, the authors introduce Metascape, a biologist-oriented portal that provides a gene list annotation, enrichment and interactome resource and enables integrated analysis of multi-OMICs datasets.

Details

Title
Metascape provides a biologist-oriented resource for the analysis of systems-level datasets
Author
Zhou Yingyao 1 ; Zhou, Bin 1 ; Pache Lars 2 ; Chang, Max 3   VIAFID ORCID Logo  ; Khodabakhshi, Alireza Hadj 1 ; Tanaseichuk Olga 1 ; Benner, Christopher 3 ; Chanda, Sumit K 2 

 Genomics Institute of the Novartis Research Foundation, San Diego, USA (GRID:grid.418185.1) (ISNI:0000 0004 0627 6737) 
 Sanford Burnham Prebys Medical Discovery Institute, Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center, La Jolla, USA (GRID:grid.479509.6) (ISNI:0000 0001 0163 8573) 
 University of California, San Diego, Department of Medicine, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) 
Publication year
2019
Publication date
Dec 2019
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2202774229
Copyright
© The Author(s) 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.