ChEA: transcription factor regulation inferred from integrating genome-wide ChIP-X experiments

ChEA: transcription factor regulation inferred from integrating genome-wide ChIP-X experiments

August 13, 2010 | Alexander Lachmann, Huilei Xu, Jayanth Krishnan, Seth I. Berger, Amin R. Mazloom and Avi Ma'ayan
The paper introduces ChIP Enrichment Analysis (ChEA), a web-based tool for integrating genome-wide ChIP-X data with mRNA expression data to infer transcription factor regulation. The authors collected and curated 189,933 interactions from 87 publications, describing the binding of 92 transcription factors to 31,932 target genes. ChEA allows users to input gene lists and compute over-representation of transcription factor targets, providing a ranked list of experiments with significant overlap. The tool also reconstructs networks of transcription factors based on shared targets and binding site proximity. Three case studies demonstrate ChEA's utility: re-analyzing breast cancer biomarker lists, re-analyzing gene expression changes in mouse embryonic stem cells, and cross-referencing ChEA with the Connectivity Map (CMAP) to design drug combinations for cancer treatment. The ChIP-X database and ChEA software are freely available online, offering a powerful resource for understanding transcriptional regulation and gene expression changes.The paper introduces ChIP Enrichment Analysis (ChEA), a web-based tool for integrating genome-wide ChIP-X data with mRNA expression data to infer transcription factor regulation. The authors collected and curated 189,933 interactions from 87 publications, describing the binding of 92 transcription factors to 31,932 target genes. ChEA allows users to input gene lists and compute over-representation of transcription factor targets, providing a ranked list of experiments with significant overlap. The tool also reconstructs networks of transcription factors based on shared targets and binding site proximity. Three case studies demonstrate ChEA's utility: re-analyzing breast cancer biomarker lists, re-analyzing gene expression changes in mouse embryonic stem cells, and cross-referencing ChEA with the Connectivity Map (CMAP) to design drug combinations for cancer treatment. The ChIP-X database and ChEA software are freely available online, offering a powerful resource for understanding transcriptional regulation and gene expression changes.
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[slides and audio] ChEA%3A transcription factor regulation inferred from integrating genome-wide ChIP-X experiments