HOMER – a one stop shop for ChIP-Seq analysis

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Presentation transcript:

HOMER – a one stop shop for ChIP-Seq analysis Graham Thomas 25th June 2015

Why do people normally use HOMER? HOMER (Hypergeometric Optimization of Motif EnRichment) is a set of tools for DNA motif discovery and over-representation analysis. Works very well to identify significantly enriched 8-20bp motifs in promoters (provide gene list) or a set of sequences (BED or Pos file) relative to genomic DNA background control. HOMER controls for CpG content in sequences to remove bias and also performs some low complexity filtering to remove nonsense results. De novo motifs are then reduced to non-redundant set, p-values for enrichment calculated, and compared against known motif library to help identify.

Other features of HOMER Peak calling DE analysis (Output file formats) UCSC/WashU visualization Basic arithmetic Peak position histogram RNA-Seq, HiC type anlaysis. One of my favorite things about HOMER is that it is very well documented

HOMER workflow HOMER FASTQ files BAM files Tag directory Visualization tracks (bedGraph / bigWig) Peak calling & merging Peak centering/extending HOMER Motif analysis Quantitation / Annotation Matrix and table generation for histograms/scatterplots GO analysis DE Analysis

findPeaks.pl 7 basic operation modes (parameters can be altered) Factor, histone, groseq, tss (5’GRO-Seq data), dnase, super, mC, Hi-C type data Calls peaks from single/multiple tag directories and generates .pos file of peaks/regions along with descriptive statistics to indicate if experiment successful. Peaks called in similar manner to MACS – using enrichment relative to 1) sequenced input control and 2) local background within sample 3) clonal amplification (PCR bias).

mergePeaks.pl annotatePeaks.pl Merges and/or compares peak position files. Will report overlapping, unique or co-bound peaks Statistics regarding significance of overlaps (based on genome size) annotatePeaks.pl Workhorse program for HOMER. Takes .pos file or BED file, alternatively option ‘TSS’ for promoter-centric analysis. Annotates features with nearby gene info -d - TagDirectory – counts reads in features -m - motif – counts motifs/ locates motif positions in features -p - peak/BED file – another way to identify overlapping features Generate histograms of read density over regions – !

makeUCSCfile.pl, makeBigWig.pl & makeMultiWigHub.pl Scripts for making files to view in genome browser included. makeMultiBigWigHub.pl creates overlay tracks getDiffExpression.pl Wrapper script for edgeR. findMotifsGenome.pl Finds de novo motifs from input peak file relative to genome/background position file.

Pipeline tools to help automation batchParallel.pl batchMakeTagDirectory.pl batchFindMotifsGenome.pl analyzeChIP-Seq.pl Wrapper for the following:- makeTagDirectory.pl makeUCSCfile.pl findPeaks.pl findMotifsGenome.pl annotatePeaks.pl

Thanks!