ArticleGigaScience2021
The Gene Expression Deconvolution Interactive Tool (GEDIT): accurate cell type quantification from gene expression data.
Article in GigaScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
- Biologic Mechanisms Underlying the Heterogeneous Response to Tight Glycemic Control among Differentially Inflamed Patients in the HALF-PINT Trial.American journal of respiratory and critical care medicine · 2025Trial
- Derivation of a peripheral blood-based transcriptomic risk score for extrapulmonary sarcoidosis.Sarcoidosis, vasculitis, and diffuse lung diseases : official journal of WASOG · 2026Article
- DeOPUS: cellular deconvolution via optimized power-transformed unmixing with shrinkage.Briefings in bioinformatics · 2026Article
- Signatures of Radiation-Induced Stress and Putative Selection on Immune Targets in Chornobyl Wolves.Molecular ecology · 2026Article
- The Spatially Resolved Kidney Transcriptome Signatures in Rat Models of Trauma-Induced Acute Kidney Injury.Kidney360 · 2026Article
- Polyunsaturated Fatty Acid Balance Modulates Microglial State in a Murine Model of Oxygen-Induced Neovascularization.Nutrients · 2026Article
- A guide to transcriptomic deconvolution in cancer.Nature reviews. Cancer · 2026Review
- Latent tuberculosis infection in high TB disease burden countries dysregulates cellular and immunological profiles which is further enhanced with uncontrolled hyperglycemia.Scientific reports · 2026Article
- Article
- Hair follicle gene expression profiling in the SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS).BMC medical genomics · 2025Article
- Circulating endothelial signatures correlate with worse outcomes in COVID-19, respiratory failure and ARDS.Critical care (London, England) · 2025Article
- Polyunsaturated fatty acid balance modulates microglial state in a murine model of oxygen-induced neovascularization.Research square · 2025Article
- Granulysin-high decidual NK cells in macaques and humans share signatures of immune defense.Cell reports · 2025Article
- Immune transcriptomic analysis on COVID-19 patients with varying clinical presentations identifies severity markers.Scientific reports · 2025Article
- An improved reference library and method for accurate cell-type deconvolution of bulk-tissue miRNA data.Nature communications · 2025Article
- Cryogenic mouse tissue homogenization as an alternative to fresh-frozen biopsy use for genomics, transcriptomics, proteomics and metabolomics.Scientific reports · 2025Article
- Identification and Validation of New Molecular Subtypes within the Early and Late Mild Cognitive Impairment Stages of Alzheimer's Disease.medRxiv : the preprint server for health sciences · 2025Article
- Article
- Transcriptomic landscape around wound bed defines regenerative versus non-regenerative outcomes in mouse digit amputation.PLoS computational biology · 2025Article
- Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundThe cell type composition of heterogeneous tissue samples can be a critical variable in both clinical and laboratory settings. However, current experimental methods of cell type quantification (e.g., cell flow cytometry) are costly, time consuming and have potential to introduce bias. Computational approaches that use expression data to infer cell type abundance offer an alternative solution. While these methods have gained popularity, most fail to produce accurate predictions for the full range of platforms currently used by researchers or for the wide variety of tissue types often studied.
resultsWe present the Gene Expression Deconvolution Interactive Tool (GEDIT), a flexible tool that utilizes gene expression data to accurately predict cell type abundances. Using both simulated and experimental data, we extensively evaluate the performance of GEDIT and demonstrate that it returns robust results under a wide variety of conditions. These conditions include multiple platforms (microarray and RNA-seq), tissue types (blood and stromal), and species (human and mouse). Finally, we provide reference data from 8 sources spanning a broad range of stromal and hematopoietic types in both human and mouse. GEDIT also accepts user-submitted reference data, thus allowing the estimation of any cell type or subtype, provided that reference data are available.
conclusionsGEDIT is a powerful method for evaluating the cell type composition of tissue samples and provides excellent accuracy and versatility compared to similar tools. The reference database provided here also allows users to obtain estimates for a wide variety of tissue samples without having to provide their own data.
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