ReviewCurrent opinion in immunology2013
Computational deconvolution: extracting cell type-specific information from heterogeneous samples.
Review in Current opinion in immunology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 174 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
174 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Pooled it
- Meta-Analysis of Maternal and Fetal Transcriptomic Data Elucidates the Role of Adaptive and Innate Immunity in Preterm Birth.Frontiers in immunology · 2018Pooled it
- Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases.Acta neuropathologica communications · 2014Pooled it
- Pooled it
- Integrative transcriptomic analysis in human and mouse model of anaphylaxis identifies gene signatures associated with cell movement, migration and neuroinflammatory signalling.Frontiers in immunology · 2022Trial
- Epithelial Cell Biomarkers Are Predictive of Response to Biologic Agents in Crohn's Disease.Inflammatory bowel diseases · 2021Trial
- Mycophenolate Mofetil Treatment of Systemic Sclerosis Reduces Myeloid Cell Numbers and Attenuates the Inflammatory Gene Signature in Skin.The Journal of investigative dermatology · 2018Trial
- Monocyte-Amplified Transcriptional Signatures of Human Diseases.bioRxiv : the preprint server for biology · 2026Article
- A large-scale DNA methylation study of alcohol use identified robust associations and cell-type specific insights.Molecular psychiatry · 2026Article
- Methylome-wide association study in blood suggests cell type-specific relationships between DNA methylation and lifetime anxiety.Nature communications · 2026Article
- Pantothenic Acid Protects Neurons After Ischemic Stroke by Targeting ID3 to Restore Action Potential Amplitude.Journal of neuroscience research · 2026Article
- Integration of Bulk and Single-Cell RNA Sequencing Analyses in Biomedicine.International journal of molecular sciences · 2026Review
- scPER: A Rigorous Computational Approach to Determine Cellular Subtypes in Tumors Aligned With Cancer Phenotypes From Total RNA Sequencing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- STRIVE: interpretable multimodal subtype discovery in Women's cancers using an attention-weighted joint variational autoencoder.Frontiers in bioinformatics · 2026Article
- New insight into RNA biomarkers in neuropathic pain: a clinician-neuroscientist roadmap to translational testing and treatment monitoring a clinical review.Frontiers in pain research (Lausanne, Switzerland) · 2026Review
- A robust workflow to benchmark deconvolution of multi-omic data.Genome biology · 2025Article
- Cell type inference in cell-free nucleic acid liquid biopsy.Nature biotechnology · 2025Review
- A machine learning model and molecular clusters of epigenetic chromatin regulators in tuberculosis based on bioinformatics and clinical samples.Scientific reports · 2025Article
- Computationally resolved neuroprogenitor cell biomarkers associate with human disorders.Stem cell reports · 2025Article
- Novel insights into post-myocardial infarction cardiac remodeling through algorithmic detection of cell-type composition shifts.PLoS genetics · 2025Article
114 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The quanta unit of the immune system is the cell, yet analyzed samples are often heterogeneous with respect to cell subsets which can mislead result interpretation. Experimentally, researchers face a difficult choice whether to profile heterogeneous samples with the ensuing confounding effects, or a priori focus on a few cell subsets of interest, potentially limiting new discoveries. An attractive alternative solution is to extract cell subset-specific information directly from heterogeneous samples via computational deconvolution techniques, thereby capturing both cell-centered and whole system level context. Such approaches are capable of unraveling novel biology, undetectable otherwise. Here we review the present state of available deconvolution techniques, their advantages and limitations, with a focus on blood expression data and immunological studies in general.
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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.