Epigenome overlap measure (EPOM) for comparing tissue/cell types based on chromatin states
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- 作者：Wei Vivian Li ; Zahra S. Razaee ; Jingyi Jessica Li
- 关键词：Comparative epigenomics ; Tissue and cell type characteristics ; Chromatin states ; Enhancers and promoters ; Histone modification ; Disease variants ; Multiple testing
- 刊名：BMC Genomics
- 出版年：2016
- 出版时间：January 2016
- 年：2016
- 卷：17
- 期：1-supp
- 全文大小：4,189 KB
- 刊物主题：Life Sciences, general; Microarrays; Proteomics; Animal Genetics and Genomics; Microbial Genetics and Genomics; Plant Genetics & Genomics;
- 出版者：BioMed Central
- ISSN：1471-2164
文摘
Background The dynamics of epigenomic marks in their relevant chromatin states regulate distinct gene expression patterns, biological functions and phenotypic variations in biological processes. The availability of high-throughput epigenomic data generated by next-generation sequencing technologies allows a data-driven approach to evaluate the similarities and differences of diverse tissue and cell types in terms of epigenomic features. While ChromImpute has allowed for the imputation of large-scale epigenomic information to yield more robust data to capture meaningful relationships between biological samples, widely used methods such as hierarchical clustering and correlation analysis cannot adequately utilize epigenomic data to accurately reveal the distinction and grouping of different tissue and cell types.