ArticleScientific reports2018
Brain Cell Type Specific Gene Expression and Co-expression Network Architectures.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 320 papers, 5 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
320 citing papers in PubMed, 5 syntheses or guidelines pooled it, 540 citations in OpenAlex.
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- Variable expression ofProceedings of the National Academy of Sciences of the United States of America · 2024Pooled it
- Cell type specific transcriptomic differences in depression show similar patterns between males and females but implicate distinct cell types and genes.Nature communications · 2023Pooled it
- Transcriptome Alterations Caused by Social Defeat Stress of Various Durations in Mice and Its Relevance to Depression and Posttraumatic Stress Disorder in Humans: A Meta-Analysis.International journal of molecular sciences · 2022Pooled it
- Spatial organization of AQP4 water channel expression in the human brain.Science advances · 2026Article
- Integration of cell-specific gene expression and chromatin accessibility facilitates localization of neurodegenerative risk in microglia.bioRxiv : the preprint server for biology · 2026Article
- Brain metastasis-associated fibroblasts shape the tumour microenvironment to enhance cancer cell invasion.Brain pathology (Zurich, Switzerland) · 2026Article
- Molecular, cellular and network mapping of brain structural deviations in patients with Post-COVID19 syndrome.Brain, behavior, & immunity - health · 2026Article
- Functional genomic profiling of schizophrenia-associated genes reveals key microglial regulators.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Article
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- Molecular Networks and Key Regulators Underlying Resilience of the Human Brain to Aging and Dementia.Biomolecules · 2026Article
- Co-expression-based models improve eQTL predictions for transcriptome-wide association studies and highlight new schizophrenia-associated genes.Nature genetics · 2026Article
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- Integration of Transcriptional Signatures from Brain Tissue and Plasma Extracellular Vesicles of a Preclinical Tauopathy Mouse Model.International journal of molecular sciences · 2026Article
- Systematic identification of cell-cell interactions associated with the severity of patients with Alzheimer's disease.Journal of Alzheimer's disease : JAD · 2026Article
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- Expanding canonical cortical cell type markers in the era of single-cell transcriptomics.Scientific reports · 2026Article
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- Shifts in protein aggregate stability define proteostasis decline in the aging human brain.bioRxiv : the preprint server for biology · 2026Article
260 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
11 authors at 4 institutions in 2 countries.
Funding
Abstract
Elucidating brain cell type specific gene expression patterns is critical towards a better understanding of how cell-cell communications may influence brain functions and dysfunctions. We set out to compare and contrast five human and murine cell type-specific transcriptome-wide RNA expression data sets that were generated within the past several years. We defined three measures of brain cell type-relative expression including specificity, enrichment, and absolute expression and identified corresponding consensus brain cell "signatures," which were well conserved across data sets. We validated that the relative expression of top cell type markers are associated with proxies for cell type proportions in bulk RNA expression data from postmortem human brain samples. We further validated novel marker genes using an orthogonal ATAC-seq dataset. We performed multiscale coexpression network analysis of the single cell data sets and identified robust cell-specific gene modules. To facilitate the use of the cell type-specific genes for cell type proportion estimation and deconvolution from bulk brain gene expression data, we developed an R package, BRETIGEA. In summary, we identified a set of novel brain cell consensus signatures and robust networks from the integration of multiple datasets and therefore transcend limitations related to technical issues characteristic of each individual study.
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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.