Nucleic Acids Research · 2019 · 203 citations · 25 references
MedicineMolecular BiologyOncologyEpigeneticsEpigenomicsMolecular OncologyCancer EpigeneticsCancer EpigenomicsCancer GenomicsDna Methylation ProfilingEpigenomic Data IntegrationMolecular Tumor ProfilingCancer Epigenetic NetworksCancer Genomics DatabasesDifferential Methylation AnalysisDna Methylation NetworksDna Methylation PatternsExpression Quantitative Trait LociGene Expression SignaturesMethylation Quantitative Trait Loci
Aberrant DNA methylation plays an important role in cancer progression. However, no resource has been available that comprehensively provides DNA methylation-based diagnostic and prognostic models, expression-methylation quantitative trait loci (emQTL), pathway activity-methylation quantitative trait loci (pathway-meQTL), differentially variable and differentially methylated CpGs, and survival analysis, as well as functional epigenetic modules for different cancers. These provide valuable information for researchers to explore DNA methylation profiles from different aspects in cancer. To this end, we constructed a user-friendly database named DNA Methylation Interactive Visualization Database (DNMIVD), which comprehensively provides the following important resources: (i) diagnostic and prognostic models based on DNA methylation for multiple cancer types of The Cancer Genome Atlas (TCGA); (ii) meQTL, emQTL and pathway-meQTL for diverse cancers; (iii) Functional Epigenetic Modules (FEM) constructed from Protein-Protein Interactions (PPI) and Co-Occurrence and Mutual Exclusive (COME) network by integrating DNA methylation and gene expression data of TCGA cancers; (iv) differentially variable and differentially methylated CpGs and differentially methylated genes as well as related enhancer information; (v) correlations between methylation of gene promoter and corresponding gene expression and (vi) patient survival-associated CpGs and genes with different endpoints. DNMIVD is freely available at http://www.unimd.org/dnmivd/. We believe that DNMIVD can facilitate research of diverse cancers.
25
Molecular signatures database (MSigDB) 3.0
Arthur Liberzon, Aravind Subramanian, Reid M. Pinchback et al. · Bioinformatics · 2011 · 7.7K citations · Full text
Jianfang Liu, Tara M. Lichtenberg, Katherine A. Hoadley et al. · Cell · 2018 · 3.9K citations · Full text
Pharmacy, Bioinformatics, Oncology +14
jvenn: an interactive Venn diagram viewer
Philippe Bardou, Jérôme Mariette, Fréderic Escudié et al. · BMC Bioinformatics · 2014 · 2.5K citations · Full text