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Series GSE37858 Query DataSets for GSE37858
Status Public on May 10, 2012
Title A Random-Forest Based Algorithm for Prediction of Enhancers From Histone Modifications
Organism Homo sapiens
Experiment type Genome binding/occupancy profiling by high throughput sequencing
Summary Transcriptional enhancers play critical roles in regulation of gene expression, but their identification has remained a challenge. Recently, it was shown that enhancers in the mammalian genome are associated with characteristic histone modification patterns, which have been increasingly exploited for enhancer identification. However, only a limited number of histone modifications have previously been investigated for this purpose, leaving the questions answered whether there exist an optimal set of histone modifications that could improve the enhancer prediction. Here, we address this issue by exploring a rich dataset produced by the human Epigenome Roadmap Project. Specifically, we examined genome-wide profiles of 24 histone modifications in human embryonic stem cells and fibroblasts, and developed a Random-Forest based algorithm to integrate histone modification profiles for identification of enhancers.As a training set, we used histone modification profiles at genome-wide binding sites of p300 in the two cell types identified using ChIP-seq. We show that this algorithm not only leads to more accurate and precise prediction of enhancers than previous methods, but also helps identify an optimal set of three chromatin marks for enhancer prediction.
 
Overall design ChIP-Seq Analysis of p300 in hESC H1 and IMR90 cells. Sequencing was done on the Illumina Genome Analyzer II platform for the H1 data and Illumina HiSeq for IMR90.Data was mapped to hg18 using Bowtie.
 
Contributor(s) Rajagopal N, Xie W, Klugman S, Kim A, Li Y, Jin F, Kuan S, Edsall L, Hawkins D, Ernst J, Ernst J, Kellis M, Stamatoyannopoulos J, Ren B
Citation(s) 23526891
Submission date May 08, 2012
Last update date Feb 12, 2020
Contact name Nisha Rajagopal
E-mail(s) nirajago@ucsd.edu
Phone 8583738328
Organization name UCSD
Lab Bing Ren
Street address 9106 REGENTS RD APT F
City LA JOLLA
State/province CA
ZIP/Postal code 92037-1445
Country USA
 
Platforms (2)
GPL9115 Illumina Genome Analyzer II (Homo sapiens)
GPL11154 Illumina HiSeq 2000 (Homo sapiens)
Samples (3)
GSM929090 ChIP_Seq_p300_IMR90
GSM929091 ChIP_Seq_Input_IMR90
GSM929092 ChIP_Seq_p300_H1
Relations
SRA SRP012970
BioProject PRJNA165163

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Supplementary file Size Download File type/resource
GSE37858_RAW.tar 259.1 Mb (http)(custom) TAR (of BED)
SRA Run SelectorHelp
Processed data provided as supplementary file
Raw data are available in SRA

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