ArticleGenome medicine2024
imply: improving cell-type deconvolution accuracy using personalized reference profiles.
Article in Genome medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Correcting spatial transcriptomics data affected by a prevalent transcript leakage problem across platforms, species, and tissues.bioRxiv : the preprint server for biology · 2026Article
- Scalable topic modelling decodes spatial tissue architecture for large-scale multiplexed imaging analysis.Nature communications · 2025Article
- scCTS: identifying the cell type-specific marker genes from population-level single-cell RNA-seq.Genome biology · 2024Article
- cypress: an R/Bioconductor package for cell-type-specific differential expression analysis power assessment.Bioinformatics (Oxford, England) · 2024Article
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Authors and funding
12 authors at 6 institutions in 1 country.
Funding
Abstract
Using computational tools, bulk transcriptomics can be deconvoluted to estimate the abundance of constituent cell types. However, existing deconvolution methods are conditioned on the assumption that the whole study population is served by a single reference panel, ignoring person-to-person heterogeneity. Here, we present imply, a novel algorithm to deconvolute cell type proportions using personalized reference panels. Simulation studies demonstrate reduced bias compared with existing methods. Real data analyses on longitudinal consortia show disparities in cell type proportions are associated with several disease phenotypes in Type 1 diabetes and Parkinson's disease. imply is available through the R/Bioconductor package ISLET at https://bioconductor.org/packages/ISLET/ .
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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.