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Epigenetic modifications, transcription factor (TF) availability and differences in chromatin folding influence how the genome is interpreted by the transcriptional machinery responsible for gene expression. Enhancers buried in non-coding regions are found to be associated with significant differences in histone marks between different cell types. In contrast, gene promoters show more uniform modifications across cell types. Here we used histone modification and chromatin-associated protein ChIP-Seq data sets in mouse embryonic stem (ES) cells as well as genomic features to identify functional enhancer regions. Using co-bound sites of OCT4, SOX2 and NANOG (co-OSN, validated enhancers) and co-bound sites of MYC and MYCN (limited enhancer activity) as enhancer positive and negative training sets, we performed multinomial logistic regression with LASSO regularization to identify key features.
Pubmed ID: 22537144 RIS Download
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Set of software modules for performing common ChIP-seq data analysis tasks across the whole genome, including positional correlation analysis, peak detection, and genome partitioning into signal-rich and signal-poor regions. The tools are designed to be simple, fast and highly modular. Each program carries out a well defined data processing procedure that can potentially fit into a pipeline framework. ChIP-Seq is also freely available on a Web interface.
View all literature mentionsSoftware ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.
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