ArticlePLoS computational biology2016
Single-Cell Co-expression Analysis Reveals Distinct Functional Modules, Co-regulation Mechanisms and Clinical Outcomes.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 57 citations in OpenAlex.
- Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data.Genome biology · 2023Pooled it
- On the same side: VISTA and its ligands interact in cis on the cell surface.Protein science : a publication of the Protein Society · 2026Article
- Cell type heterogeneity in gene co-expression networks: implications for toxicological research.Briefings in bioinformatics · 2025Review
- Gene set optimization for single cell transcriptomics.Computational intelligence methods for bioinformatics and biostatistics : ... international meeting, CIBB ... : revised selected papers. CIBB (Meeting) · 2025Article
- Leveraging cell type-specificity for gene set analysis of single cell transcriptomics.bioRxiv : the preprint server for biology · 2024Article
- Cell type evolution reconstruction across species through cell phylogenies of single-cell RNA sequencing data.Nature ecology & evolution · 2024Article
- siVAE: interpretable deep generative models for single-cell transcriptomes.Genome biology · 2023Article
- A multimodal deep learning model to infer cell-type-specific functional gene networks.BMC bioinformatics · 2023Article
- Weighted Gene Co-Expression Network Analysis (WGCNA) Discovered Novel Long Non-Coding RNAs for Polycystic Ovary Syndrome.Biomedicines · 2023Article
- Gut Microbiota Alterations in Trace Amine-Associated Receptor 9 (TAAR9) Knockout Rats.Biomolecules · 2022Article
- SpaceX: gene co-expression network estimation for spatial transcriptomics.Bioinformatics (Oxford, England) · 2022Article
- scGENA: A Single-Cell Gene Coexpression Network Analysis Framework for Clustering Cell Types and Revealing Biological Mechanisms.Bioengineering (Basel, Switzerland) · 2022Article
- Deeper insights into long-term survival heterogeneity of pancreatic ductal adenocarcinoma (PDAC) patients using integrative individual- and group-level transcriptome network analyses.Scientific reports · 2022Article
- Risk subtyping and prognostic assessment of prostate cancer based on consensus genes.Communications biology · 2022Article
- Linking co-expression modules with phenotypes.Bioinformation · 2022Article
- Single-cell transcriptome atlas of human mesenchymal stem cells exploring cellular heterogeneity.Clinical and translational medicine · 2021Article
- Mutant IDH1 promotes phagocytic function of microglia/macrophages in gliomas by downregulating ICAM1.Cancer letters · 2021Article
- Article
- Comprehensive network modeling from single cell RNA sequencing of human and mouse reveals well conserved transcription regulation of hematopoiesis.BMC genomics · 2020Article
- Nuclear gene proximity and protein interactions shape transcript covariations in mammalian single cells.Nature communications · 2020Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
Co-expression analysis has been employed to predict gene function, identify functional modules, and determine tumor subtypes. Previous co-expression analysis was mainly conducted at bulk tissue level. It is unclear whether co-expression analysis at the single-cell level will provide novel insights into transcriptional regulation. Here we developed a computational approach to compare glioblastoma expression profiles at the single-cell level with those obtained from bulk tumors. We found that the co-expressed genes observed in single cells and bulk tumors have little overlap and show distinct characteristics. The co-expressed genes identified in bulk tumors tend to have similar biological functions, and are enriched for intrachromosomal interactions with synchronized promoter activity. In contrast, single-cell co-expressed genes are enriched for known protein-protein interactions, and are regulated through interchromosomal interactions. Moreover, gene members of some protein complexes are co-expressed only at the bulk level, while those of other complexes are co-expressed at both single-cell and bulk levels. Finally, we identified a set of co-expressed genes that can predict the survival of glioblastoma patients. Our study highlights that comparative analyses of single-cell and bulk gene expression profiles enable us to identify functional modules that are regulated at different levels and hold great translational potential.
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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.