ENCODE Encyclopedia, Version 0.3 (Archived): Overview

Gene expression (RNA-seq)

The expression levels of genes and transcripts annotated by GENCODE in over 200 human and 90 mouse experiments.
[ Bulk RNA-seq Data | Query | Download | Method ]

Transcription factor binding (TF ChIP-seq)

Peaks (enriched genomic regions) of TFs computed from ~900 human and mouse ChIP-seq experiments.
[ Raw Data | Peaks ]
Visualize sequence motifs and other information [ Factorbook ]

Histone mark enrichment (ChIP-seq)

Peaks of a variety of histone marks computed from ~600 ChIP-seq experiments. 
[ Raw Data | Peaks ]

Open chromatin (DNase-seq)

DNase I hypersensitive sites (also known as DNase-seq peaks) computed from ~300 human and mouse experiments. 
[ Raw Data | Peaks ]

Topologically associating domains (TADs) and compartments (Hi-C)

TADs and A and B compartments computed from 12 human cell lines.
[ Raw Data | Visualize ]

Promoter-enhancer links (ChIA-PET)

Links between promoters and distal regulatory elements such as enhancers computed from 8 ChIA-PET experiments.
[ Raw Data | Links ]

RNA binding protein occupancy (eCLIP-seq)

Peaks computed from eCLIP-seq data in human cell lines K562 and HepG2 for a large number of RNA Binding Proteins (RBPs).
[ Raw Data | Peaks ]

Promoter-like regions

DNase hypersensitivity and histone modification H3K4me3 are well-known indicators of promoter function. We have developed an unsupervised method that combines DNase and H3K4me3 signals in the same cell type to predict promoter-like regions. When used to predict ranked gene expression from RNA-seq data, our method shows higher accuracy than DNase and H3K4me3 individually. We have applied this method to 107 human cell types and 14 mouse cell types with both DNase and H3K4me3 data generated by the ENCODE and Roadmap Epigenomic consortia. For cell and tissues types with only H3K4me3 data, we centered predictions on H3K4me3 peaks and ranked them by H3K4me3 signals. You can query these promoter-like regions by genomic locations, nearby genes, or SNPs, and visualize them in the UCSC and WashU genome browsers.
[ Visualize | | Method ]

Enhancer-like regions

DNase hypersensitivity and histone modification H3K27ac are well-known indicators of enhancer function. We have developed an unsupervised method that combines DNase and H3K27ac signals in the same cell type to predict enhancer-like regions. When tested on mouse transgenic assays, our method shows higher accuracy than DNase and H3K27ac individually. We have applied this method to 47 human cell types and 14 mouse cell types with both DNase and H3K27ac data generated by the ENCODE and Roadmap Epigenomic consortia. For cell and tissues types with only H3K27ac or DNase data, we rank the peaks using the available data and make predictions of enhancer-like regions. You can query these enhancers by genomic locations, nearby genes, or SNPs, and visualize them in the UCSC and WashU genome browsers.
[ Visualize | Method ]

Enhancer-like genomic regions were tested on VISTA experimentally-validated enhancer elements: [ VISTA ]

Chromatin states

Semi-automated genomic annotation methods such as ChromHMM and Segway take as input a panel of epigenomic data (including histone mark ChIP-seq and DNase-seq) in a particular cell type and use machine learning methods to simultaneously partition the genome into segments and assign chromatin states to these segments; the states are assigned such that two segments with the same state exhibit similar epigenomic patterns. The procedure is "semi-automated" because states are then manually compared with known biological information in order to designate each state as an enhancer-like, promoter-like, gene body, etc.
[ Search ]

Variant Annotation

Over the past decade, Genome Wide Association Studies (GWAS) have provided insights into how genetic variations contribute to human diseases. However, over 80% of the variants reported by GWAS are in noncoding regions of the genome and the mechanism of how they contribute to disease onset is unknown. By integrating data from the ENCODE project and other public sources, RegulomeDB and HaploReg are two resources developed by ENCODE labs to aid the research community in annotating GWAS variants. FunSeq is another ENCODE resource for annotating both germline and somatic variants, particularly in the noncoding regions of cancer genomes.
[ RegulomeDB | HaploReg | FunSeq ]