calculateKmerEnrichment {transite} | R Documentation |
Calls computeKmerEnrichment
to compute k-mer
enrichment values
for multiple foregrounds. Calculates enrichment for foreground sets in
parallel.
calculateKmerEnrichment(foreground.sets, background.set, k, permutation = FALSE, chisq.p.value.threshold = 0.05, p.adjust.method = "BH", n.cores = 4)
foreground.sets |
list of foreground sets; a foreground set is a
character vector of
DNA or RNA sequences (not both) and a strict subset of the
|
background.set |
character vector of DNA or RNA sequences that constitute the background set |
k |
length of k-mer, either |
permutation |
if |
chisq.p.value.threshold |
threshold below which Fisher's exact test is used instead of Pearson's chi-squared test |
p.adjust.method |
see |
n.cores |
number of computing cores to use |
A list with two entries:
(1) dfs: a list of data frames with results from
computeKmerEnrichment
for each of the foreground sets
(2) kmers: a character vector of all k-mers
Other k-mer functions: checkKmers
,
computeKmerEnrichment
,
drawVolcanoPlot
,
empiricalEnrichmentMeanCDF
,
generateKmers
,
generatePermutedEnrichments
,
homopolymerCorrection
,
permTestGeometricMean
,
runKmerSPMA
, runKmerTSMA
# define simple sequence sets for foreground and background foreground.set1 <- c( "CAACAGCCUUAAUU", "CAGUCAAGACUCC", "CUUUGGGGAAU", "UCAUUUUAUUAAA", "AAUUGGUGUCUGGAUACUUCCCUGUACAU", "AUCAAAUUA", "AGAU", "GACACUUAAAGAUCCU", "UAGCAUUAACUUAAUG", "AUGGA", "GAAGAGUGCUCA", "AUAGAC", "AGUUC", "CCAGUAA" ) foreground.set2 <- c("UUAUUUA", "AUCCUUUACA", "UUUUUUU", "UUUCAUCAUU") foreground.sets <- list(foreground.set1, foreground.set2) background.set <- c(foreground.set1, foreground.set2, "CCACACAC", "CUCAUUGGAG", "ACUUUGGGACA", "CAGGUCAGCA") # single-threaded kmer.enrichment.values.st <- calculateKmerEnrichment(foreground.sets, background.set, 6, n.cores = 1) ## Not run: # multi-threaded kmer.enrichment.values.mt <- calculateKmerEnrichment(foreground.sets, background.set, 6) ## End(Not run)