NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis

Author:

Zhou Guangyan1,Soufan Othman1,Ewald Jessica2,Hancock Robert E W3,Basu Niladri2,Xia Jianguo14ORCID

Affiliation:

1. Institute of Parasitology, McGill University, Montreal, Quebec, Canada

2. Department of Natural Resource Sciences, McGill University, Montreal, Quebec, Canada

3. Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada

4. Department of Animal Science, McGill University, Montreal, Quebec, Canada

Abstract

Abstract The growing application of gene expression profiling demands powerful yet user-friendly bioinformatics tools to support systems-level data understanding. NetworkAnalyst was first released in 2014 to address the key need for interpreting gene expression data within the context of protein-protein interaction (PPI) networks. It was soon updated for gene expression meta-analysis with improved workflow and performance. Over the years, NetworkAnalyst has been continuously updated based on community feedback and technology progresses. Users can now perform gene expression profiling for 17 different species. In addition to generic PPI networks, users can now create cell-type or tissue specific PPI networks, gene regulatory networks, gene co-expression networks as well as networks for toxicogenomics and pharmacogenomics studies. The resulting networks can be customized and explored in 2D, 3D as well as Virtual Reality (VR) space. For meta-analysis, users can now visually compare multiple gene lists through interactive heatmaps, enrichment networks, Venn diagrams or chord diagrams. In addition, users have the option to create their own data analysis projects, which can be saved and resumed at a later time. These new features are released together as NetworkAnalyst 3.0, freely available at https://www.networkanalyst.ca.

Funder

Natural Sciences and Engineering Research Council of Canada

Canada Research Chairs

Publisher

Oxford University Press (OUP)

Subject

Genetics

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