ArticleGenome biology2014
MethylPurify: tumor purity deconvolution and differential methylation detection from single tumor DNA methylomes.
Article in Genome biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed.
- MethylBERT enables read-level DNA methylation pattern identification and tumour deconvolution using a Transformer-based model.Nature communications · 2025Article
- Inferring tumor purity using multi-omics data based on a uniform machine learning framework MoTP.Briefings in bioinformatics · 2024Article
- Tumor purity estimated from bulk DNA methylation can be used for adjusting beta values of individual samples to better reflect tumor biology.NAR genomics and bioinformatics · 2024Article
- CelFiE-ISH: a probabilistic model for multi-cell type deconvolution from single-molecule DNA methylation haplotypes.Genome biology · 2024Article
- Computational deconvolution of DNA methylation data from mixed DNA samples.Briefings in bioinformatics · 2024Review
- Challenges and perspectives in computational deconvolution of genomics data.Nature methods · 2024Review
- A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing.Nature communications · 2024Article
- Genomic hypomethylation in cell-free DNA predicts responses to checkpoint blockade in lung and breast cancer.Scientific reports · 2023Article
- Deconvolution of immune cell composition and biological age of hepatocellular carcinoma using DNA methylation.Methods (San Diego, Calif.) · 2023Article
- ExosomePurity: tumour purity deconvolution in serum exosomes based on miRNA signatures.Briefings in bioinformatics · 2023Article
- A revision of the InfiniumPurify R package for genome-wide correction of tumor purity in Infinium DNA methylation array data.Genes & diseases · 2023Article
- Cell-type Deconvolution and Age Estimation Using DNA Methylation Reveals NK Cell Deficiency in the Hepatocellular Carcinoma Microenvironment.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022Article
- Spatial heterogeneity in DNA methylation and chromosomal alterations in diffuse gliomas and meningiomas.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2022Article
- Glioma Shapes Blood-Brain Barrier Integrity and Remodels the Tumor Microenvironment: Links with Clinical Features and Prognosis.Journal of clinical medicine · 2022Article
- Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes.Briefings in bioinformatics · 2022Article
- MeConcord: a new metric to quantitatively characterize DNA methylation heterogeneity across reads and CpG sites.Bioinformatics (Oxford, England) · 2022Article
- A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution.Nature methods · 2022Article
- Obtaining spatially resolved tumor purity maps using deep multiple instance learning in a pan-cancer study.Patterns (New York, N.Y.) · 2022Article
- Tumor purity adjusted beta values improve biological interpretability of high-dimensional DNA methylation data.PloS one · 2022Article
- Transcriptome analysis reveals high tumor heterogeneity with respect to re-activation of stemness and proliferation programs.PloS one · 2022Article
Corrections and comments
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Authors and funding
18 authors.
Funding
Abstract
We propose a statistical algorithm MethylPurify that uses regions with bisulfite reads showing discordant methylation levels to infer tumor purity from tumor samples alone. MethylPurify can identify differentially methylated regions (DMRs) from individual tumor methylome samples, without genomic variation information or prior knowledge from other datasets. In simulations with mixed bisulfite reads from cancer and normal cell lines, MethylPurify correctly inferred tumor purity and identified over 96% of the DMRs. From patient data, MethylPurify gave satisfactory DMR calls from tumor methylome samples alone, and revealed potential missed DMRs by tumor to normal comparison due to tumor heterogeneity.
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