ArticlePLoS computational biology2015
Sharing and Specificity of Co-expression Networks across 35 Human Tissues.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 111 papers, 1 of them a synthesis that pooled it.
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Who cites it
111 citing papers in PubMed, 1 synthesis or guideline pooled it, 197 citations in OpenAlex.
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- Large-scale, interpretable gene regulatory network inference through biologically informed matrix factorization.bioRxiv : the preprint server for biology · 2026Article
- Diffusion-based representation integration for foundation models improves spatial transcriptomics analysis.Bioinformatics (Oxford, England) · 2026Article
- Multiomic analysis identifies glutaminolysis-dependent metabolic enhancement of immune memory utilised for vaccine development.Nature communications · 2026Article
- Strategies for constructing context-specific protein-protein interaction networks.Briefings in bioinformatics · 2026Review
- Translation efficiency covariation identifies conserved coordination patterns across cell types.Nature biotechnology · 2026Article
- A tissue-specific atlas of protein-protein associations enables prioritization of candidate disease genes.Nature biotechnology · 2026Article
- Challenges and Opportunities in Single-Sample Network Modeling.bioRxiv : the preprint server for biology · 2026Article
- Diffusion-based Representation Integration for Foundation Models Improves Spatial Transcriptomics Analysis.bioRxiv : the preprint server for biology · 2026Article
- A comparison of computational methods for expression forecasting.Genome biology · 2025Article
- Combining Motifs, CRE Activity, And Gene Expression Data Using ML Greatly Improves the Accuracy of Tissue-Specific TF Network Maps.bioRxiv : the preprint server for biology · 2025Article
- Endometrial receptivity profiled through transcriptomic analysis of uterine fluid extracellular vesicles using systems biology and bayesian modeling for pregnancy prediction.Scientific reports · 2025Article
- Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networks.Genome research · 2025Article
- Dissecting the cellular architecture and genetic circuitry of the soybean seed.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
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- scGraph2Vec: a deep generative model for gene embedding augmented by graph neural network and single-cell omics data.GigaScience · 2024Article
- Current and future directions in network biology.Bioinformatics advances · 2024Article
- Gene Co-Expression Analysis of Multiple Brain Tissues Reveals Correlation of FAM222A Expression with Multiple Alzheimer's Disease-Related Genes.Journal of Alzheimer's disease : JAD · 2024Article
- Article
51 more citing papers are in PubMed but not listed here.
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
Abstract
To understand the regulation of tissue-specific gene expression, the GTEx Consortium generated RNA-seq expression data for more than thirty distinct human tissues. This data provides an opportunity for deriving shared and tissue specific gene regulatory networks on the basis of co-expression between genes. However, a small number of samples are available for a majority of the tissues, and therefore statistical inference of networks in this setting is highly underpowered. To address this problem, we infer tissue-specific gene co-expression networks for 35 tissues in the GTEx dataset using a novel algorithm, GNAT, that uses a hierarchy of tissues to share data between related tissues. We show that this transfer learning approach increases the accuracy with which networks are learned. Analysis of these networks reveals that tissue-specific transcription factors are hubs that preferentially connect to genes with tissue specific functions. Additionally, we observe that genes with tissue-specific functions lie at the peripheries of our networks. We identify numerous modules enriched for Gene Ontology functions, and show that modules conserved across tissues are especially likely to have functions common to all tissues, while modules that are upregulated in a particular tissue are often instrumental to tissue-specific function. Finally, we provide a web tool, available at mostafavilab.stat.ubc.ca/GNAT, which allows exploration of gene function and regulation in a tissue-specific manner.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.