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: | Andrew E. Teschendorff, Tianyu Zhu, Charles E. Breeze, Stephan Beck |
---|---|
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 |
Similar Items
-
Identifying key DNA methylation sites and their cis-methylation quantitative loci for intramuscular fatty acid traits using genome and methylome data in Yorkshire pigs
by: Qi Shen, et al.
Published: (2023-12-01) -
MBD-seq - realities of a misunderstood method for high-quality methylome-wide association studies
by: Karolina A. Aberg, et al.
Published: (2020-04-01) -
Genome-wide analysis of DNA methylation and risk of cardiovascular disease in a Chinese population
by: Yan Gao, et al.
Published: (2021-05-01) -
An Efficient and Flexible Method for Deconvoluting Bulk RNA-Seq Data with Single-Cell RNA-Seq Data
by: Xifang Sun, et al.
Published: (2019-09-01) -
Reliability of DNA methylation measures using Illumina methylation BeadChip
by: Zongli Xu, et al.
Published: (2021-05-01)