get.enriched.motif: get.enriched.motif to identify the overrepresented motifs in...

In lijingya/ELMER: Inferring Regulatory Element Landscapes and Transcription Factor Networks Using Cancer Methylomes

Description

get.enriched.motif is a function make use of Probes.motif data from ELMER.data package to calculate the motif enrichment Odds Ratio and 95% confidence interval for a given set of probes. If save is TURE, two output files will be saved: getMotif.XX.enriched.motifs.rda and getMotif.XX.motif.enrichment.csv (see detail).

Usage

get.enriched.motif(probes.motif, probes, background.probes, lower.OR = 1.1, min.incidence = 10, 
dir.out = "./", label = NULL, save=TRUE)

Arguments

probes.motif	A matrix contains motifs occurrence within probes regions. Probes.motif in ELMER.data will be used if probes.motif is missing (detail see Probes.motif).
probes	A vector lists the name of probes to define the set of probes in which motif enrichment OR and confidence interval will be calculated.
background.probes	A vector lists name of probes which are considered as background for motif.enrichment calculation (see detail).
lower.OR	A number specifies the smallest lower boundary of 95% confidence interval for Odds Ratio. The motif with higher lower boudnary of 95% confidence interval for Odds Ratio than the number are the significantly enriched motifs (detail see reference).
min.incidence	A non-negative integer specifies the minimum incidence of motif in the given probes set. 10 is default.
dir.out	A path specifies the directory for outputs. Default is current directory
label	A character labels the outputs such as "hypo", "hyper"
save	If save is TURE, two files will be saved: getMotif.XX.enriched.motifs.rda and getMotif.XX.motif.enrichment.csv (see detail).

Details

background.probes: For enhancer study, it is better to use probes within distal enhancer probes as background.probes. For promoter study, it is better to use probes within promoter regions as background.probes. Because enhancer and promoter have different CG content and harbors different clusters of TFs motif.

save: if save is TRUE, two files will be save on the disk. The first file is getMotif.XX.motif.enrichment.csv (XX depends on option label). This file reports the Odds Ratio and 95% confidence interval for these Odds Ratios which pass the signficant cutoff (lower.OR and min.incidence). The second file is getMotif.XX.enriched.motifs.rda (XX depends on option lable). This file contains a list R object with enriched motifs as name and probes containing the enriched motif as contents. This object will be used in get.TFs function. if save is FALSE, the function will return a R object which is the same with second file.

Value

A list (R object) with enriched motifs as name and probes containing the enriched motif as contents. And hypo.motif.enrichment.pdf plot will be generated.

Author(s)

Lijing Yao (maintainer: [e-mail])

References

Yao L, Shen H, Laird PW, Farnham PJ,Berman BP: Inferring Regulatory Element Landscapes and Transcription Factor Networks from Cancer Methylomes. in revision of Genome Biology

Examples

probes <- c("cg00329272","cg10097755","cg08928189", "cg17153775","cg21156590",
"cg19749688","cg12590404","cg24517858","cg00329272","cg09010107",
"cg15386853", "cg10097755", "cg09247779","cg09181054","cg19371916")
load(system.file("extdata","mee.example.rda",package = "ELMER"))
bg <- rownames(getMeth(mee))
enriched.motif <- get.enriched.motif(probes=probes,background.probes = bg,
min.incidence=2, label="hypo")

lijingya/ELMER documentation built on May 21, 2019, 6:14 a.m.