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

Description Usage Arguments Details Value Examples

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

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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

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## 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.