ADEPTUS: A discovery tool for disease prediction, enrichment and network analysis based on profiles from many diseases

David Amar, Amir Vizel, Carmit Levy, Ron Shamir*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Motivation Large-scale publicly available genomic data on many disease phenotypes could improve our understanding of the molecular basis of disease. Tools that undertake this challenge by jointly analyzing multiple phenotypes are needed. Results ADEPTUS is a web-tool that enables various functional genomics analyses based on a high-quality curated database spanning >38, 000 gene expression profiles and >100 diseases. It offers four types of analysis. (i) For a gene list provided by the user it computes disease ontology (DO), pathway, and gene ontology (GO) enrichment and displays the genes as a network. (ii) For a given disease, it enables exploration of drug repurposing by creating a gene network summarizing the genomic events in it. (iii) For a gene of interest, it generates a report summarizing its behavior across several studies. (iv) It can predict the tissue of origin and the disease of a sample based on its gene expression or its somatic mutation profile. Such analyses open novel ways to understand new datasets and to predict primary site of cancer.

Original languageEnglish
Pages (from-to)1959-1961
Number of pages3
JournalBioinformatics
Volume34
Issue number11
DOIs
StatePublished - 1 Jun 2018

Funding

FundersFunder number
Bella Walter Memorial Fund of the Israel Cancer Association
ISF-NSFC
Edmond J. Safra Center for Ethics, Harvard University
Horizon 2020 Framework Programme726225
European Research Council
Israel Science Foundation317/13
Tel Aviv University

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