get.permu: get.permu to generate permutation results for calculation of...

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

Description

get.permu is a function to use the same statistic model to calculate random enhancer-gene pairs. Based on the permutation value, empirical P value can be calculated for the real enhancer-gene pair (see reference).

Usage

get.permu(mee, geneID, percentage = 0.2, rm.probes = NULL,
portion = 0.3, permu.size = 10000, permu.dir = NULL, cores = NULL)

Arguments

mee	A MEE.data object contains at least meth, exp, probeInfo, geneInfo.
geneID	A vector lists gene id which need to be have permutation.
percentage	A number ranges from 0 to 1 specifying the percentage of samples of control and experimental groups used to link probes to genes. Default is 0.2.
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.
rm.probes	A vector lists name of probes which belongs to the set of probes fed into get.pair function.
permu.size	A number specifies the number of permuation. Default is 1000.
permu.dir	A path shows the directory of permutation outputs
cores	A interger which defines the number of cores to be used in parallel process. Default is NULL: no parallel process.

Value

Certain number of permutation for each gene of interets.

Note

Permutation is the most time consuming step. It is recommended to use multiple cores for this step. Default permutation time is 1000 which may need 12 hrs by 4 cores. However 10,000 permutations is recommended to get high confidence results. But it may cost 2 days.

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"))
permu <-get.permu(mee=mee,geneID=rownames(getExp(mee)),
                  rm.probes=c("cg00329272","cg10097755"),
                  permu.size=5)

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