ArticleNature communications2022
Comprehensive evaluation of deconvolution methods for human brain gene expression.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.
What it found
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Who cites it
88 citing papers in PubMed.
- Transcriptome Analysis of Hippocampus After Weekly Binge Alcohol Exposure and Voluntary Exercise in Rats.Alcohol, clinical & experimental research · 2026Article
- IECP: iterative equilibration of cell-type expression profiles improves accuracy of reference-free deconvolution.Bioinformatics (Oxford, England) · 2026Article
- Same-Slide Spatial Multiomics Integration with IN-DEPTH Reveals Tumor Virus-Linked Spatial Reorganization of the Tumor Microenvironment.Cancer discovery · 2026Article
- cellGeometry: ultra-fast single-cell deconvolution of bulk RNA-Seq using a geometric solution.Nature communications · 2026Article
- Transcriptomic Traces of Noise Exposure in Hearing Loss and Systematic Identification of Biomarker Candidates at the Molecular Scale.International journal of molecular sciences · 2026Article
- Integrating single-cell and single-nucleus datasets improves bulk RNA-seq deconvolution.Cell reports methods · 2026Article
- Shifts in protein aggregate stability define proteostasis decline in the aging human brain.bioRxiv : the preprint server for biology · 2026Article
- Current landscape of single-cell genomics in meningioma.Neuro-oncology advances · 2026Review
- A transcriptomic dimension of neuronal and immune gene programs within the subgenual anterior cingulate cortex in schizophrenia.Translational psychiatry · 2026Article
- A guide to transcriptomic deconvolution in cancer.Nature reviews. Cancer · 2026Review
- Deconvolution Methods to Link Multi-Omics Data to Cell Type-Specific Extracellular Vesicle Abundances.Proteomics · 2026Review
- omnideconv: a unifying framework for using and benchmarking single-cell-informed deconvolution of bulk RNA-seq data.Genome biology · 2026Article
- Non-negative matrix factorization and deconvolution as a dual simplex problem.Genome biology · 2026Article
- Artificial Intelligence Revolution in Transcriptomics: From Single Cells to Spatial Atlases.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Integrative Transcriptomic Analysis and Preliminary Peripheral Blood Evaluation IdentifyInternational journal of general medicine · 2026Article
- A robust workflow to benchmark deconvolution of multi-omic data.Genome biology · 2025Article
- Article
- Extracellular Vesicles From Multiple Sclerosis White Matter Exhibit Synaptic, Mitochondrial, Complement and Ageing-Related Pathway Dysregulation.Journal of extracellular vesicles · 2025Article
- Deep learning-based cell type profiles reveal signatures of Alzheimer's disease resilience and resistance.Brain : a journal of neurology · 2025Article
- BLEND: probabilistic cellular deconvolution with individualized single-cell reference integration.Genome biology · 2025Article
28 more citing papers are in PubMed but not listed here.
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Authors and funding
8 authors.
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Abstract
Transcriptome deconvolution aims to estimate the cellular composition of an RNA sample from its gene expression data, which in turn can be used to correct for composition differences across samples. The human brain is unique in its transcriptomic diversity, and comprises a complex mixture of cell-types, including transcriptionally similar subtypes of neurons. Here, we carry out a comprehensive evaluation of deconvolution methods for human brain transcriptome data, and assess the tissue-specificity of our key observations by comparison with human pancreas and heart. We evaluate eight transcriptome deconvolution approaches and nine cell-type signatures, testing the accuracy of deconvolution using in silico mixtures of single-cell RNA-seq data, RNA mixtures, as well as nearly 2000 human brain samples. Our results identify the main factors that drive deconvolution accuracy for brain data, and highlight the importance of biological factors influencing cell-type signatures, such as brain region and in vitro cell culturing.
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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.