ChIP-seq 核心分析 下游分析

http://icb.med.cornell.edu/wiki/index.php/Elementolab/ChIPseeqer_Tutorial

 【怪毛匠子 整理】

ChIP-seq【核心分析 下游分析】

• Core Analysis : Peak detection: Split raw data then run ChIPseeqer
• Core Analysis : Quality Control: QC analysis for the raw reads (after Split raw data)
• Core Analysis : Gene-level annotation of peaks (Exons/introns/promoters/downstream extremities) and genomic distribution using ChIPseeqerAnnotate
• Core Analysis : Quick promoters summary of peaks using ChIPseeqerSummaryPromoters
• Core Analysis : Create data tracks for the UCSC Genome Browser
• Visualize peak locations in UCSC Genome Browser using ChIPseeqerPeaksTrack
• Create a read density track for the UCSC Genome Browser using ChIPseeqerMakeReadDensityTrack
• Core Analysis : Use ChIPseeqerRun if you want to run the 3 first steps of the Core Analysis (QC, Split in reads-Peak detection, Gene annotation) fast with a single command.
• Extended Analysis : Nongenic annotation using ChIPseeqerNongenicAnnotate
• Extended Analysis : RNAGenes annotation using ChIPseeqerRNAGenes
• Extended Analysis : Motif discovery
• De novo regulatory element discovery using ChIPseeqerFIRE and FIRE
• Find peak matches to known transcription factor binding sites using ChIPseeqerMotifMatch
• Extended Analysis : Pathways analysis
• Look for enriched pathways using ChIPseeqeriPAGE and iPAGE
• Find pathway matches to peaks/genes using ChIPseeqerPathwayMatch
• Extended Analysis : Evaluate conservation of peaks using ChIPseeqerCons
• Extended Analysis : Estimate average read density profiles in genes or peak regions using ChIPseeqerDensityMatrix
• Extended Analysis : Extract (maximum/average) reads count for peak regions across multiple ChIP-seq datasets using ChIPseeqerReadCountMatrix
• Extended Analysis : Cluster and visualize the detected peak regions using ChIPseeqerCluster
• Extended Analysis - Compare datasets : Compare two lists of peaks; (e.g., Which peaks overlap ? Are there any peaks in the first list with no overlap in the second one?)
• Use CompareIntervals
• Extended Analysis - Compare datasets : Compare two lists of RefSeq genes (e.g., Which genes are common in the two lists?)
• Use CompareGenes
• Extended Analysis - Compare datasets : Make a similarity coefficient matrix (based on Jaccard index) to see which TFs are similar in terms of peaks overlapping, using ChIPseeqerComputeJaccardIndex
• Extended Analysis - Compare datasets : Make one matrix for each genepart (promoters/exons/introns/distal etc) from multiple peak files in order to find e.g., genes promoters where most of the TFs bind. 
• ChIPseeqerMakeGenepartsMatrix

Other supplementary tools can be found here