ArticleGenome biology2019
TOAST: improving reference-free cell composition estimation by cross-cell type differential analysis.
Article in Genome biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.
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Who cites it
64 citing papers in PubMed.
- Trial
- DeOPUS: cellular deconvolution via optimized power-transformed unmixing with shrinkage.Briefings in bioinformatics · 2026Article
- IECP: iterative equilibration of cell-type expression profiles improves accuracy of reference-free deconvolution.Bioinformatics (Oxford, England) · 2026Article
- iDCF: Interpretable deconvolution of cell fractions via biologically-informed deep learning using scRNA-seq data.PLoS computational biology · 2026Article
- Integration of Bulk and Single-Cell RNA Sequencing Analyses in Biomedicine.International journal of molecular sciences · 2026Review
- A guide to transcriptomic deconvolution in cancer.Nature reviews. Cancer · 2026Review
- Multi-Scale Transcriptomics Redefining the Tumor Immune Microenvironment.Biotech (Basel (Switzerland)) · 2026Review
- Non-negative matrix factorization and deconvolution as a dual simplex problem.Genome biology · 2026Article
- A robust workflow to benchmark deconvolution of multi-omic data.Genome biology · 2025Article
- Machine Learning Models for Cancer Research: A Narrative Review of Bulk RNA-Seq Applications.International journal of molecular sciences · 2025Review
- Common DNA sequence variation influences epigenetic aging in African populations.Communications biology · 2025Article
- Cell-type-specific and inflammatory DNA methylation patterns associated with PTSD.Brain, behavior, and immunity · 2025Article
- Predicting immune responsiveness in ER-positive breast cancer for personalized therapy: a population-based study.NPJ precision oncology · 2025Article
- Approaching the holistic transcriptome-convolution and deconvolution in transcriptomics.Briefings in bioinformatics · 2025Review
- PoweREST: Statistical power estimation for spatial transcriptomics experiments to detect differentially expressed genes between two conditions.PLoS computational biology · 2025Article
- Novel insights into post-myocardial infarction cardiac remodeling through algorithmic detection of cell-type composition shifts.PLoS genetics · 2025Article
- ARTdeConv: adaptive regularized tri-factor non-negative matrix factorization for cell type deconvolution.NAR genomics and bioinformatics · 2025Article
- Robustness and resilience of computational deconvolution methods for bulk RNA sequencing data.Briefings in bioinformatics · 2025Article
- Examining cellular heterogeneity in human DNA methylation studies: Overview and recommendations.STAR protocols · 2025Review
- A systematic evaluation of cell-type-specific differential methylation analysis in bulk tissue.Briefings in bioinformatics · 2025Article
4 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors.
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Abstract
In the analysis of high-throughput data from complex samples, cell composition is an important factor that needs to be accounted for. Except for a limited number of tissues with known pure cell type profiles, a majority of genomics and epigenetics data relies on the "reference-free deconvolution" methods to estimate cell composition. We develop a novel computational method to improve reference-free deconvolution, which iteratively searches for cell type-specific features and performs composition estimation. Simulation studies and applications to six real datasets including both DNA methylation and gene expression data demonstrate favorable performance of the proposed method. TOAST is available at https://bioconductor.org/packages/TOAST .
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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.