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FACER (Functional Atlas of Chromatin Epigenetic Regulators) is a compilation of prioritized functional CRs across multiple cancer types, involving their specific functions, biological categories and their roles in cancers. Functional CRs for each cancer type were prioritized by integrating their various features in multiple omics, including the activity (mutation ratio and extent of differential expression), regulation strength from both TF and miRNAs, central roles in protein-protein interaction network and regulation to epigenetic modifications (DNA hyper- and hypomethylation) of CRs. Moreover, according to the prevalence of CRs across cancers, three types of CRs were proposed, including cancer-common, cancer-specific and mixed CRs. FACER contains 640 functional CRs across 33 cancer types. Users could search the interest CR or interest cancer type or both, the results will exhibited the basic biological information, the related cancer types and the detailed multi-omics functional features in the interest cancer type of the corresponding CR. FACER offers the search and download for basic information and multi-omics features of 640 functional CRs across 33 cancer types. For a better display and full functionality of our database, please use Google Chrome or Opera.

We proposed a computational method to prioritize the functional CRs in each cancer type by integrating multi-omics features of CRs, which mainly involved three steps. Firstly, we proposed seven functional features to respectively characterize the activity, regulation strength from both differentially expressed TFs and miRNAs, central roles in PPIN and aberrant regulation to epigenetic modifications of CRs. The activity of CRs was assessed from their mutation ratio and the extent of differential expression in tumor samples. On the other hand, we evaluated the aberrant regulation activity of CRs by their regulation effect on DNA hyper- and hypomethylation level. Then CRs were ranked based on these seven features in each cancer type. Secondly, we constructed classifiers to prioritize functional CRs for each cancer type based on the aggregated ranks by integrating the seven separate ranks using robust rank aggregation (RRA) method. The aggregated ranks represent the systematic function importance of CRs. Using the cancer hallmark related CRs as the golden standard data set, we trained the classifiers based on all possible feature combinations for individual cancer types. Finally, we selected the most effective combined feature (MECF) and obtained the corresponding optimal functional CRs for each cancer type.

Users can input a CR of interest (e.g. KMT2C) or choose one type of cancer (e.g. Kidney Renal Papillary Cell Carcinoma) to view the informations of CR. In addition, users can input a CR of interest (e.g. KMT2C) and choose one type of cancer (e.g. Kidney Renal Papillary Cell Carcinoma) to view the informations of CR.

In the results page, we provide id, symbol, category, hm subcategory, DNAm subcategory, cancer type, rank, frequency and type of CR user interested. In addition, user can get the sum of results. User also can see the details of CR by clicking details.

In the details page, we provide all informations of CR you selected.

We provide 'Cancer-common CRs and their related cancer types:Cancer-common CR.xlsx', 'Cancer-specific CRs and their related cancer types:Cancer-specific CR.xlsx', and 'Functional CRs across 33 cancer types:Functional CRs across 33 cancer types.xlsx' for users to download.