Description

This track shows probable locations of the specified histone modifications in the given cell types as determined by chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq). Each experiment is associated with an input signal which represents the control condition where immunoprecipitation with non-specific immunoglobulin was performed in the same cell type. For each experiment (cell type vs. antibody), this track shows a graph of enrichment for histone modification (Signal) along with sites that have the greatest evidence of histone modification, as identified by the PeakSeq algorithm (Peaks).

The sequence reads, quality scores, and alignment coordinates from these experiments are available for download.

Display Conventions and Configuration

This track is a multi-view composite track that contains multiple data types (views). For each view, there are multiple subtracks that display individually on the browser. Instructions for configuring multi-view tracks are here. This track contains the following views:

Peaks

Regions of signal enrichment based on processed data (normalized data from pooled replicates). ENCODE Peaks tables contain fields for statistical significance, including FDR (qValue).

Signal

Density graph (wiggle) of signal enrichment based on processed data.

Methods

Cells were grown according to the approved ENCODE cell culture protocols. For details on the chromatin immunoprecipitation protocol used, see Euskirchen et al. (2007), Rozowsky et al. (2009) and Auerbach et al. (2009).

DNA recovered from the precipitated chromatin was sequenced on the Illumina (Solexa) sequencing platform and mapped to the genome using the Eland alignment program. ChIP-seq data was scored based on sequence reads (length ~30 bp) that align uniquely to the human genome. From the mapped tags, a signal map of ChIP DNA fragments (average fragment length ~200 bp) was constructed where the signal height was the number of overlapping fragments at each nucleotide position in the genome.

For each 1 Mb segment of each chromosome, a peak height threshold was determined by requiring a false discovery rate <= 0.01 when comparing the number of peaks above said threshold to the number of peaks obtained from multiple simulations of a random null background with the same number of mapped reads (also accounting for the fraction of mapable bases for sequence tags in that 1 Mb segment). The number of mapped tags in a putative binding region was compared to the normalized (normalized by correlating tag counts in genomic 10 kb windows) number of mapped tags in the same region from an input DNA control. Using a binomial test, only regions that had a p-value <= 0.01 were considered to be significantly enriched compared to the input DNA control.

Release Notes

This is Release 2 (August 2012). It contains a total of 12 new experiments on histone modifications including 1 new cell line and 5 new antibodies.

Errata

At the request of the data provider, data files and table related to experiment wgEncodeEM003324 (H3K27ac in MEL cells) have been removed. An incorrect antibody was used in this experiment.

Credits

These data were generated and analyzed by the labs of Michael Snyder at Stanford University and Sherman Weissman at Yale University.   

Contact: Philip Cayting

References

Auerbach RK, Euskirchen G, Rozowsky J, Lamarre-Vincent N, Moqtaderi Z, Lefrançois P, Struhl K, Gerstein M, Snyder M. Mapping accessible chromatin regions using Sono-Seq. Proc Natl Acad Sci U S A. 2009 Sep 1;106(35):14926-31.

Euskirchen GM, Rozowsky JS, Wei CL, Lee WH, Zhang ZD, Hartman S, Emanuelsson O, Stolc V, Weissman S, Gerstein MB et al. Mapping of transcription factor binding regions in mammalian cells by ChIP: comparison of array- and sequencing-based technologies. Genome Res. 2007 Jun;17(6):898-909.

Martone R, Euskirchen G, Bertone P, Hartman S, Royce TE, Luscombe NM, Rinn JL, Nelson FK, Miller P, Gerstein M et al. Distribution of NF-kappaB-binding sites across human chromosome 22. Proc Natl Acad Sci U S A. 2003 Oct 14;100(21):12247-52.

Robertson G, Hirst M, Bainbridge M, Bilenky M, Zhao Y, Zeng T, Euskirchen G, Bernier B, Varhol R, Delaney A et al. Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nat Methods. 2007 Aug;4(8):651-7.

Rozowsky J, Euskirchen G, Auerbach RK, Zhang ZD, Gibson T, Bjornson R, Carriero N, Snyder M, Gerstein MB. PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls. Nat Biotechnol. 2009 Jan;27(1):66-75.

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