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
