EPISCORE: cell type deconvolution of bulk tissue DNA methylomes from single-cell RNA-Seq data
Abstract Cell type heterogeneity presents a challenge to the interpretation of epigenome data, compounded by the difficulty in generating reliable single-cell DNA methylomes for large numbers of cells and samples. We present EPISCORE, a computational algorithm that performs virtual microdissection o...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2020-09-01
|
| Series: | Genome Biology |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13059-020-02126-9 |
| _version_ | 1819052164306173952 |
|---|---|
| author | Andrew E. Teschendorff Tianyu Zhu Charles E. Breeze Stephan Beck |
| author_facet | Andrew E. Teschendorff Tianyu Zhu Charles E. Breeze Stephan Beck |
| author_sort | Andrew E. Teschendorff |
| collection | DOAJ |
| description | Abstract Cell type heterogeneity presents a challenge to the interpretation of epigenome data, compounded by the difficulty in generating reliable single-cell DNA methylomes for large numbers of cells and samples. We present EPISCORE, a computational algorithm that performs virtual microdissection of bulk tissue DNA methylation data at single cell-type resolution for any solid tissue. EPISCORE applies a probabilistic epigenetic model of gene regulation to a single-cell RNA-seq tissue atlas to generate a tissue-specific DNA methylation reference matrix, allowing quantification of cell-type proportions and cell-type-specific differential methylation signals in bulk tissue data. We validate EPISCORE in multiple epigenome studies and tissue types. |
| first_indexed | 2024-12-21T12:15:29Z |
| format | Article |
| id | doaj.art-76ab0e631ac94341bf74cbd9db289243 |
| institution | Directory Open Access Journal |
| issn | 1474-760X |
| language | English |
| last_indexed | 2024-12-21T12:15:29Z |
| publishDate | 2020-09-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj.art-76ab0e631ac94341bf74cbd9db2892432022-12-21T19:04:28ZengBMCGenome Biology1474-760X2020-09-0121113310.1186/s13059-020-02126-9EPISCORE: cell type deconvolution of bulk tissue DNA methylomes from single-cell RNA-Seq dataAndrew E. Teschendorff0Tianyu Zhu1Charles E. Breeze2Stephan Beck3CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of SciencesCAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of SciencesAltius Institute for Biomedical SciencesUCL Cancer Institute, Paul O’Gorman Building, University College LondonAbstract Cell type heterogeneity presents a challenge to the interpretation of epigenome data, compounded by the difficulty in generating reliable single-cell DNA methylomes for large numbers of cells and samples. We present EPISCORE, a computational algorithm that performs virtual microdissection of bulk tissue DNA methylation data at single cell-type resolution for any solid tissue. EPISCORE applies a probabilistic epigenetic model of gene regulation to a single-cell RNA-seq tissue atlas to generate a tissue-specific DNA methylation reference matrix, allowing quantification of cell-type proportions and cell-type-specific differential methylation signals in bulk tissue data. We validate EPISCORE in multiple epigenome studies and tissue types.http://link.springer.com/article/10.1186/s13059-020-02126-9DNA methylationEWASSingle-cell RNA-Seq |
| spellingShingle | Andrew E. Teschendorff Tianyu Zhu Charles E. Breeze Stephan Beck EPISCORE: cell type deconvolution of bulk tissue DNA methylomes from single-cell RNA-Seq data Genome Biology DNA methylation EWAS Single-cell RNA-Seq |
| title | EPISCORE: cell type deconvolution of bulk tissue DNA methylomes from single-cell RNA-Seq data |
| title_full | EPISCORE: cell type deconvolution of bulk tissue DNA methylomes from single-cell RNA-Seq data |
| title_fullStr | EPISCORE: cell type deconvolution of bulk tissue DNA methylomes from single-cell RNA-Seq data |
| title_full_unstemmed | EPISCORE: cell type deconvolution of bulk tissue DNA methylomes from single-cell RNA-Seq data |
| title_short | EPISCORE: cell type deconvolution of bulk tissue DNA methylomes from single-cell RNA-Seq data |
| title_sort | episcore cell type deconvolution of bulk tissue dna methylomes from single cell rna seq data |
| topic | DNA methylation EWAS Single-cell RNA-Seq |
| url | http://link.springer.com/article/10.1186/s13059-020-02126-9 |
| work_keys_str_mv | AT andreweteschendorff episcorecelltypedeconvolutionofbulktissuednamethylomesfromsinglecellrnaseqdata AT tianyuzhu episcorecelltypedeconvolutionofbulktissuednamethylomesfromsinglecellrnaseqdata AT charlesebreeze episcorecelltypedeconvolutionofbulktissuednamethylomesfromsinglecellrnaseqdata AT stephanbeck episcorecelltypedeconvolutionofbulktissuednamethylomesfromsinglecellrnaseqdata |