get.pair: get.pair to predict enhancer-gene linkages.

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

Description

get.pair is a function to predict enhancer-gene linkages using associations between DNA methylation at enhancer CpG sites and expression of 20 nearby genes of the CpG sites (see reference). Two files will be saved if save is true: getPair.XX.all.pairs.statistic.csv and getPair.XX.pairs.significant.csv (see detail).

Usage

get.pair(mee, probes, nearGenes, percentage = 0.2, permu.size = 10000, permu.dir = NULL, 
Pe = 0.001, dir.out = "./", diffExp = FALSE, cores = NULL, portion=0.3,   
label = NULL, save=TRUE)

Arguments

mee	A MEE.data object contains at least meth, exp, probeInfo, geneInfo slots.
probes	A vector lists name of probes that need to be linked to genes.
nearGenes	A list (R object) containing output of GetNearGenes function or a path of XX.rda file containing output of GetNearGenes function.
percentage	A number ranges from 0 to 1 specifying the percentage of samples of methylated and unmethylated groups used to link probes to genes. Default is 0.2.
permu.size	A number specifies the number of permuation. Default is 1000.
permu.dir	A path shows the directory of permutation outputs.
Pe	A number specifies the empircal pvalue cutoff for defining signficant pairs. Default is 0.01
portion	A number specify the cut point to define binary methlation level for probe loci. Default is 0.3. When beta value is above 0.3, the probe is methylated and vice versa. For one probe, the percentage of methylated or unmethylated samples should be above 0.05.
dir.out	A path specifies the directory for outputs of get.pair function. Default is current directory
diffExp	A logic. Default is FALSE. If TRUE, t test will be applied to test whether putative target gene are differentially expressed between two control and experimental groups.
cores	A interger which defines the number of cores to be used in parallel process. Default is NULL: no parallel process.
label	A character labels the outputs.
save	A logic. If save is true, two files will be saved for publication or analysis re-usage purpose: getPair.XX.all.pairs.statistic.csv and getPair.XX.pairs.significant.csv (see detail)

Details

save: When save is TRUE, function will generate two XX.csv files. The first one is named getPair.XX.all.pairs.statistic.csv ( XX depends on option label). This file contains all statistic results for each probe-gene pair. Based on this file, user can change different P value or sig.dir cutoff to select the significant results without redo the analysis. The second file is named getPair.XX.pairs.significant.csv (XX depends on option label). This file contains statistic results for the probes that pass the significant criteria (Pe). When save is FALSE, a data frame R object will be generate which contains the same information with the second file.

Value

A data frame contains statistic result for significant pairs

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

load(system.file("extdata","mee.example.rda",package = "ELMER"))
nearGenes <-GetNearGenes(TRange=getProbeInfo(mee,probe=c("cg00329272","cg10097755")),
                         geneAnnot=getGeneInfo(mee))
                         Hypo.pair <-get.pair(mee=mee,probes=c("cg00329272","cg10097755"),
                                              nearGenes=nearGenes,permu.size=5,Pe = 0.2,
                                              dir.out="./",
                                              label= "hypo")

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