ArticleBioinformatics (Oxford, England)2020
Using multiple measurements of tissue to estimate subject- and cell-type-specific gene expression.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Transcriptomic Analysis and Multiple Machine Learning Approaches Identify ZDHHC20 and Its Highly Correlated Gene AK5 as Biomarkers in Multiple System Atrophy.Journal of molecular neuroscience : MN · 2026Article
- Pan-cancer neural regulation pattern with implications for patient stratification and immunotherapy.Molecular therapy. Nucleic acids · 2025Article
- Unico: a unified model for cell-type resolution genomics from heterogeneous omics data.Genome biology · 2025Article
- BLEND: probabilistic cellular deconvolution with individualized single-cell reference integration.Genome biology · 2025Article
- Cell type heterogeneity in gene co-expression networks: implications for toxicological research.Briefings in bioinformatics · 2025Review
- Penalised regression improves imputation of cell-type specific expression using RNA-seq data from mixed cell populations compared to domain-specific methods.PLoS computational biology · 2025Article
- Human endogenous retrovirus W in multiple sclerosis: transcriptional activity is associated with decline in oligodendrocyte proportions in the white matter of the brain.Journal of neurovirology · 2024Article
- Disentangling transcriptomic heterogeneity within the human subgenual anterior cingulate cortex.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- ACCURATE ESTIMATION OF RARE CELL-TYPE FRACTIONS FROM TISSUE OMICS DATA VIA HIERARCHICAL DECONVOLUTION.The annals of applied statistics · 2024Article
- Effect of age and sex differences on the abundances of neuronal, glial, and endothelial cells in non-diseased brain tissue.PloS one · 2024Article
- Identification of pan-cancer/testis genes and validation of therapeutic targeting in triple-negative breast cancer: Lin28a-based and Siglece-based vaccination induces antitumor immunity and inhibits metastasis.Journal for immunotherapy of cancer · 2023Article
- Herpesvirus Infections in the Human Brain: A Neural Cell Model of the Complement System Derived from Induced Pluripotent Stem Cells.Current topics in behavioral neurosciences · 2023Article
- Spatiotemporal and genetic regulation of A-to-I editing throughout human brain development.Cell reports · 2022Article
- Cellular and genetic drivers of RNA editing variation in the human brain.Nature communications · 2022Article
- Robust and accurate estimation of cellular fraction from tissue omics data via ensemble deconvolution.Bioinformatics (Oxford, England) · 2022Article
- Psychosis in Alzheimer's Disease Is Associated With Increased Excitatory Neuron Vulnerability and Post-transcriptional Mechanisms Altering Synaptic Protein Levels.Frontiers in neurology · 2022Article
- Bayesian estimation of cell type-specific gene expression with prior derived from single-cell data.Genome research · 2021Article
- DeCompress: tissue compartment deconvolution of targeted mRNA expression panels using compressed sensing.Nucleic acids research · 2021Article
- Transcriptome alterations are enriched for synapse-associated genes in the striatum of subjects with obsessive-compulsive disorder.Translational psychiatry · 2021Article
- Recovering Spatially-Varying Cell-Specific Gene Co-expression Networks for Single-Cell Spatial Expression Data.Frontiers in genetics · 2021Article
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Authors and funding
3 authors.
Funding
Abstract
motivationPatterns of gene expression, quantified at the level of tissue or cells, can inform on etiology of disease. There are now rich resources for tissue-level (bulk) gene expression data, which have been collected from thousands of subjects, and resources involving single-cell RNA-sequencing (scRNA-seq) data are expanding rapidly. The latter yields cell type information, although the data can be noisy and typically are derived from a small number of subjects.
resultsComplementing these approaches, we develop a method to estimate subject- and cell-type-specific (CTS) gene expression from tissue using an empirical Bayes method that borrows information across multiple measurements of the same tissue per subject (e.g. multiple regions of the brain). Analyzing expression data from multiple brain regions from the Genotype-Tissue Expression project (GTEx) reveals CTS expression, which then permits downstream analyses, such as identification of CTS expression Quantitative Trait Loci (eQTL). AVAILABILITY AND IMPLEMENTATION: We implement this method as an R package MIND, hosted on https://github.com/randel/MIND. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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