an integrated pipeline for the genome-wide analysis of transcription factor binding sites from chip-seq一个集成的管道的全基因组分析从chip-seq转录因子结合位点.pdfVIP

An Integrated Pipeline for the Genome-Wide Analysis of Transcription Factor Binding Sites from ChIP-Seq 1. 1,2. 3. 4 5 6 Eloi Mercier , Arnaud Droit , Leping Li , Gordon Robertson , Xuekui Zhang , Raphael Gottardo * 1 Computational Biology Unit, Institut de Recherche Clinique de Montreal, Montreal, Canada, 2 Department of Molecular Medecine, Faculty of Medicine, Endocrinology and Genomics, Centre de Recherche du CHUQ (CRCHUQ), Laval University, Quebec, Canada, 3 Biostatistics Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina, United States of America, 4 BC Cancer Agency, Genome Sciences Centre, Vancouver, Canada, 5 Department of Statistics, University of British Columbia, Vancouver, Canada, 6 Vaccine and Infections Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America Abstract ChIP-Seq has become the standard method for genome-wide profiling DNA association of transcription factors. To simplify analyzing and interpreting ChIP-Seq data, which typically involves using multiple applications, we describe an integrated, open source, R-based analysis pipeline. The pipeline addresses data input, peak detection, sequence and motif analysis, visualization, and data export, and can readily be extended via other R and Bioconductor packages. Using a standard multicore computer, it can be used with datasets consisting of tens of thousands of enriched regions. We demonstrate its effectiveness on published human ChIP-Seq datasets for FOXA1, ER, CTCF and STAT1, where it detected co-occurring motifs that were consistent with the literature but not detected by other metho