eepiCOLOC was implemented in a web-based tool with built-in large-scale and context-dependent epigenomics annotations. The epigenomics profiles were indexed using GIGGLE (https://github.com/ryanlayer/giggle). The web server was developed by Python, jQuery, igv.js, amcharts.js and related JavaScript modules.
High-throughput genome-wide epigenomic assays, such as ChIP-seq, DNase-seq and ATAC-seq, have profiled a huge amount of functional elements across numerous human tissues/cell types, which provides an unprecedented opportunity to interpret human genome and disease in context-dependent manner. Colocalization analysis determine whether genomic features are functionally related to given search and will facilitate to identify the underlying biological functions charactering intricate relationship with query genomic regions. Existing colocalization methods used diverse assumptions and background models to assess the significance of enrichment, however, they only provided limited predefined sets of genomic feature. Here, we comprehensively collected and integrated over 44,385 bulk or single cell epigenomic assays across 53 human tissues/cell types, such as transcription factor binding, histone modification, open chromatin and transcriptional event. By classifying these profiles into hierarchy of tissue/cell type, we developed a web portal for users to perform context-dependent colocalization analysis in a convenient way.
epiCOLOC (http://mulinlab.org/epicoloc) was developed by mulinlab@Research Center of Basic Medical Sciences, Tianjin Medical University. If you have questions or suggestions to this platform, please contact us through mulinliATconnect.hku.hk