ChIP-Atlas(https://chip-atlas.org/)提供了一套用于分析表观基因组景观的数据挖掘工具,由超过376.000个公共ChIP-seq的全面集成提供动力,ATAC-seq,来自六种代表性模型生物的DNase-seq和亚硫酸氢盐-seq实验。为了解开染色质结构的复杂性,它介导了细胞内转录和表型多样性的调节组引发的产生,我们报告了ChIP-Atlas3.0通过在新合并的“注释轨道”部分中纳入基因组和表观基因组特征的其他轨道,从而增强了清晰度。轨迹包括染色体构象(Hi-C和eQTL数据集),转录调控元件(ChromHMM和FANTOM5增强子),以及与疾病和表型相关的基因组变异(GWASSNP和ClinVar变异)。这些注释轨道与其他实验轨道一起很容易访问,促进更好地阐明转录和表型性状多样化的染色质结构。此外,\'差异分析,\'一个新的在线工具,比较查询表观基因组数据以识别差异结合,可访问,和使用ChIP-seq的甲基化区域,ATAC-seq和DNase-seq,和亚硫酸氢盐-SEQ数据集,分别。注释轨道和差异分析工具的集成,加上持续的数据扩展,使ChIP-Atlas3.0成为挖掘转录调控机制景观的强大资源,从而提供有价值的观点,特别是遗传疾病研究和药物发现。
ChIP-Atlas (https://chip-atlas.org/) presents a suite of data-mining tools for analyzing epigenomic landscapes, powered by the comprehensive integration of over 376 000 public ChIP-seq, ATAC-seq, DNase-seq and Bisulfite-seq experiments from six representative model organisms. To unravel the intricacies of chromatin architecture that mediates the regulome-initiated generation of transcriptional and phenotypic diversity within cells, we report ChIP-Atlas 3.0 that enhances clarity by incorporating additional tracks for genomic and epigenomic features within a newly consolidated \'annotation track\' section. The tracks include chromosomal conformation (Hi-C and eQTL datasets), transcriptional regulatory elements (ChromHMM and FANTOM5 enhancers), and genomic variants associated with diseases and phenotypes (GWAS SNPs and ClinVar variants). These annotation tracks are easily accessible alongside other experimental tracks, facilitating better elucidation of chromatin architecture underlying the diversification of transcriptional and phenotypic traits. Furthermore, \'Diff Analysis,\' a new online tool, compares the query epigenome data to identify differentially bound, accessible, and methylated regions using ChIP-seq, ATAC-seq and DNase-seq, and Bisulfite-seq datasets, respectively. The integration of annotation tracks and the Diff Analysis tool, coupled with continuous data expansion, renders ChIP-Atlas 3.0 a robust resource for mining the landscape of transcriptional regulatory mechanisms, thereby offering valuable perspectives, particularly for genetic disease research and drug discovery.