This track represents a comprehensive set of human transcription factor binding sites based on ChIP-seq experiments generated by production groups in the ENCODE Consortium between February 2011 and November 2018.
Transcription factors (TFs) are proteins that bind to DNA and interact with RNA polymerases to regulate gene expression. Some TFs contain a DNA binding domain and can bind directly to specific short DNA sequences ('motifs'); others bind to DNA indirectly through interactions with TFs containing a DNA binding domain. High-throughput antibody capture and sequencing methods (e.g. chromatin immunoprecipitation followed by sequencing, or 'ChIP-seq') can be used to identify regions of TF binding genome-wide. These regions are commonly called ChIP-seq peaks.
The related Transcription Factor ChIP-seq Clusters tracks (hg19, -hg38) +hg38) provide summary views of this data.
The display for this track shows site location with the point-source of the peak marked with a colored vertical bar and the level of enrichment at the site indicated by the darkness of the item. The subtracks are colored by UCSC ENCODE 2 cell type color conventions on the hg19 assembly, and by similarity of cell types in DNaseI hypersensitivity assays (as in the DNase Signal) track in the hg38 assembly.
The display can be filtered to higher valued items, using the Score range: configuration item. The score values were computed at UCSC based on signal values assigned by the ENCODE pipeline. The input signal values were multiplied by a normalization factor calculated as the ratio of the maximum score value (1000) to the signal value at 1 standard deviation from the mean, with values exceeding 1000 capped at 1000. This has the effect of distributing scores up to mean + 1std across the score range, but assigning all above to the maximum score.
The ChIP-seq peaks in this track were generated by the the ENCODE Transcription Factor ChIP-seq Processing Pipeline. Methods documentation and full metadata for each track can be found at the ENCODE project portal, using The ENCODE file accession (ENCFF*) listed in the track label.
Thanks to the ENCODE Consortium, the ENCODE ChIP-seq production laboratories, and the ENCODE Data Coordination Center for generating and processing the datasets used here. Special thanks to Henry Pratt, Jill Moore, Michael Purcaro, and Zhiping Weng, PI, at the ENCODE Data Analysis Center (ZLab at UMass Medical Center) for providing the peak datasets, metadata, and guidance developing this track.
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