Article

Systematic assessment of the biological impact of cellular deconvolution on downstream analyses of disease transcriptomes

2026-08-11

Abstract excerpt

<h4>Background</h4> Cellular deconvolution methods estimate cell-type proportions from bulk RNA-seq data, typically using single-cell RNA-seq–derived signatures, enabling separation of disease-associated transcriptional changes into composition-driven and cell-intrinsic effects. However, these approaches depend on model assumptions and the stability of cell-type signatures, and it remains unclear how deconvolutio...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: d1da7497-2acf-5026-9e55-a5210037f8b2
DOI: 10.64898/2026.08.05.742993

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Systematic assessment of the biological impact of cellular deconvolution on downstream analyses of disease transcriptomesDOI 10.64898/2026.08.05.742993Read

Deciphering cellular transcriptional alterations in Alzheimer’s disease brainsSemantic proximity Read

Deconvolving the contributions of cell-type heterogeneity on cortical gene expression.Semantic proximity Read

Single-cell multiomics reveals disrupted glial gene regulatory programs in Alzheimer’s disease via interpretable machine learningSemantic proximity Read

Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic dataSemantic proximity Read

Cell-type specific inference from bulk RNA-sequencing data by integrating single cell reference profiles via EPIC-unmixSemantic proximity Read

Single-cell deconvolution of 3,000 post-mortem brain samples for eQTL and GWAS dissection in mental disordersSemantic proximity Read

A computational method for direct imputation of cell type-specific expression profiles and cellular compositions from bulk-tissue RNA-Seq in brain disordersSemantic proximity Read

Genetic variants associated with Alzheimer's disease confer different cerebral cortex cell-type population structureSemantic proximity Read

Spatial Dissection of the Distinct Cellular Responses to Normal Aging and Alzheimer’s Disease in Human Prefrontal Cortex at Single-Nucleus ResolutionSemantic proximity Read

Combinatorial analyses reveal cellular composition changes have different impacts on transcriptomic changes of cell type specific genes in Alzheimer’s DiseaseSemantic proximity Read

Estimating cell compositions and cell-type-specific expressions from GWAS data using invariant causal prediction, deep learning and regularized matrix completionSemantic proximity Read

Human brain single nucleus cell type enrichments in neurodegenerative diseasesSemantic proximity Read