ArticleGenome research2020
Untangling the effects of cellular composition on coexpression analysis.
Article in Genome research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- DeOPUS: cellular deconvolution via optimized power-transformed unmixing with shrinkage.Briefings in bioinformatics · 2026Article
- Evaluation of analysis modes for RNA coexpression in single-cell and bulk tissue.bioRxiv : the preprint server for biology · 2026Article
- Cell type heterogeneity in gene co-expression networks: implications for toxicological research.Briefings in bioinformatics · 2025Review
- Identifying reproducible transcription regulator coexpression patterns with single cell transcriptomics.PLoS computational biology · 2025Article
- Single-cell network biology enabling cell-type-resolved disease genetics.Genomics & informatics · 2025Review
- Accelerating crop improvement via integration of transcriptome-based network biology and genome editing.Planta · 2025Review
- Augmenting the human interactome for disease prediction through gene networks inferred from human cell atlas.Animal cells and systems · 2025Article
- Alzheimer's disease rewires gene coexpression networks coupling different brain regions.NPJ systems biology and applications · 2024Article
- Transcriptome organization of white blood cells through gene co-expression network analysis in a large RNA-seq dataset.Frontiers in immunology · 2024Article
- Deep topographic proteomics of a human brain tumour.Nature communications · 2023Article
- Comparative single-cell transcriptomic analysis of primate brains highlights human-specific regulatory evolution.Nature ecology & evolution · 2023Article
- Investigating trait variability of gene co-expression network architecture in brain by controlling for genomic risk of schizophrenia.PLoS genetics · 2023Article
- Convergent coexpression of autism-associated genes suggests some novel risk genes may not be detectable in large-scale genetic studies.Cell genomics · 2023Article
- Imputation of single-cell transcriptome data enables the reconstruction of networks predictive of breast cancer metastasis.Computational and structural biotechnology journal · 2023Article
- Prioritizing de novo autism risk variants with calibrated gene- and variant-scoring models.Human genetics · 2022Article
- In search of a Drosophila core cellular network with single-cell transcriptome data.G3 (Bethesda, Md.) · 2022Article
- Shared regulation and functional relevance of local gene co-expression revealed by single cell analysis.Communications biology · 2022Article
- Elucidating gene expression patterns across multiple biological contexts through a large-scale investigation of transcriptomic datasets.BMC bioinformatics · 2022Article
- ThePlant direct · 2022Article
- Robust normalization and transformation techniques for constructing gene coexpression networks from RNA-seq data.Genome biology · 2022Article
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2 authors.
Funding
Abstract
Coexpression analysis is widely used for inferring regulatory networks, predicting gene function, and interpretation of transcriptome profiling studies, based on methods such as clustering. The majority of such studies use data collected from bulk tissue, where the effects of cellular composition present a potential confound. However, the impact of composition on coexpression analysis has not been studied in detail. Here, we examine this issue for the case of human RNA analysis. Focusing on brain tissue, we found that, for most genes, differences in expression levels across cell types account for a large fraction of the variance of their measured RNA levels (median
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