Differential Expression Enrichment Tool (DEET): an interactive atlas of human differential gene expression

Author:

Sokolowski Dustin J12,Ahn Jedid123,Erdman Lauren13,Hou Huayun1,Ellis Kai12,Wang Liangxi12,Goldenberg Anna1345,Wilson Michael D12ORCID

Affiliation:

1. Genetics and Genome Biology, SickKids Research Institute , Toronto, ON, Canada

2. Department of Molecular Genetics, University of Toronto , Toronto, ON, Canada

3. Department of Computer Science, University of Toronto , Toronto, ON, Canada

4. Vector Institute , Toronto, ON, Canada

5. CIFAR , Toronto, ON, Canada

Abstract

AbstractDifferential gene expression analysis using RNA sequencing (RNA-seq) data is a standard approach for making biological discoveries. Ongoing large-scale efforts to process and normalize publicly available gene expression data enable rapid and systematic reanalysis. While several powerful tools systematically process RNA-seq data, enabling their reanalysis, few resources systematically recompute differentially expressed genes (DEGs) generated from individual studies. We developed a robust differential expression analysis pipeline to recompute 3162 human DEG lists from The Cancer Genome Atlas, Genotype-Tissue Expression Consortium, and 142 studies within the Sequence Read Archive. After measuring the accuracy of the recomputed DEG lists, we built the Differential Expression Enrichment Tool (DEET), which enables users to interact with the recomputed DEG lists. DEET, available through CRAN and RShiny, systematically queries which of the recomputed DEG lists share similar genes, pathways, and TF targets to their own gene lists. DEET identifies relevant studies based on shared results with the user's gene lists, aiding in hypothesis generation and data-driven literature review.

Funder

NSERC

Canada Research Chairs Program

NSERC CGS M, PGS D and Ontario Graduate Scholarships

Genome Canada Genomics Technology Platform

Centre for Applied Genomics

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Computer Science Applications,Genetics,Molecular Biology,Structural Biology

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