%0 Journal Article
%T Integrative analysis with expanded DNA methylation data reveals common key regulators and pathways in cancers
%A Jianxiong Tang
%A Kai Zhang
%A Mengchi Wang
%A Nan Li
%A Rizi Ai
%A Shicai Fan
%A Wei Du
%A Wei Wang
%A Ying Zhao
%J Archive of "NPJ Genomic Medicine".
%D 2019
%R 10.1038/s41525-019-0077-8
%X The workflow of the integrative analysis and the EAGLING model. a The multi-omics data of 13 cancers from TCGA were used to identify the genes that are differentially expressed and differentially methylated and also contain somatic mutations (i.e. triple-evidenced genes) in each cancer. Pan-cancer analysis revealed that the triple-evidenced genes shared by a majority of the 13 cancers include many previously identified biomarkers or therapeutic targets. b In the model construction, two features are used to build the logistic regression model: the methylation level of the closest CpG based on 450£¿K array and the methylation value from the WGBS of the corresponding CpG from the tissue that has the most similar local methylation profile with the site to be predicte
%U https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358616/