pathenrich: Enrichment analysis to identify putative pathways of interest...

In ewymathe/testALTREinstall: Workflow for Identifying Regulatory Elements from Chromatin Accessibility Assay Data

Description

Determine which pathways are overrepresented in altered promoters and enhancers. Pathways are determined by linking the enhancer/promoter to the nearest gene, and then linking genes to pathways using the gene ontology database. The 'gene' argument limits how few genes a pathway can contain, while the 'offspring' argument limits how many offspring a pathway can contain. Pathways with low gene counts are less reliable (often false positives), while pathways with many offspring are vague and unlikely to be of much use – the enrichment of their more precise offspring is the more interesting question.

Usage

pathenrich(analysisresults, ontoltype = "MF", enrichpvalfilt = 0.01,
  lfctypespecific = 1.5, lfcshared = 1.2, pvaltypespecific = 0.01,
  pvalshared = 0.05, genes = 20, offspring = 300,
  regionsubset = "promoter")

Arguments

analysisresults	Results from analysis of counts, categaltre_peaks.
ontoltype	One of three categories: 'MF' (molecular function), 'CC' (cellular component), 'BP' (biological process).
enrichpvalfilt	Adjusted pval for enrichment to filter on (adjusted for multiple testing).
lfctypespecific	Log2fold change (of chromatin accessibility) for type specific enhancers/promoters.
lfcshared	Log2fold change (of chromatin accessibility) for shared enhancers/promoters.
pvaltypespecific	P-value (of chromatin accessibility) for type specific enhancers/promoters.
pvalshared	P-value (of chromatin accessibility) for shared enhancers/promoters.
genes	Minimum number of genes allowable in a pathway.
offspring	Maximum number of offspring allowable in a pathway.
regionsubset	A 'promoter' or 'enhancer'.

Details

************CHANGE ANALYSISRESULTS TO ALTREPEAKS!!!!****************** ****************CHANGE REGIONSUBSET TO REGIONTYPE!!!!*****************

Value

dataframe identifying p-values for enriched pathways – pathways also annotated with additional information

Examples

## Not run: 
dir <- system.file('extdata', package='ALTRE', mustWork=TRUE)
csvfile <- file.path(dir, 'lung.csv')
sampleinfo <- loadCSVFile(csvfile)
samplePeaks <- loadBedFiles(sampleinfo)
consPeaks <- getConsensusPeaks(samplepeaks=samplePeaks,minreps=2)
TSSannot <- getTSS()
consPeaksAnnotated <- combineAnnotatePeaks(conspeaks = consPeaks,
                                          TSS = TSSannot,
                                          merge = TRUE,
                                          regionspecific = TRUE,
                                          mergedistenh = 1500,
                                          mergedistprom = 1000 )
#Need to run getcounts on all chromosomes
counts_consPeaks <- getCounts(annotpeaks = consPeaksAnnotated,
                             sampleinfo = sampleinfo,
                             reference = 'SAEC')
altre_peaks <- countanalysis(counts=counts_consPeaks,
                             pval=0.01,
                             lfcvalue=1)
MFenrich <- pathenrich(analysisresults = altre_peaks,
                       ontoltype = 'MF',
                       enrichpvalfilt = 0.01)
BPenrich <- pathenrich(analysisresults=altre_peaks,
                       ontoltype='BP',
                       enrichpvalfilt=0.01)

## End(Not run)

ewymathe/testALTREinstall documentation built on May 16, 2019, 9:42 a.m.