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

In 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(data,
          geneID,
          methy = NULL,
          unmethy = NULL,
          percentage = 0.2,
          rm.probes = NULL,
          correlation = "negative",
          permu.size = 10000,
          permu.dir = NULL,
          cores = 1)

Arguments

data	A multiAssayExperiment with DNA methylation and Gene Expression data. See createMAE function.
geneID	A vector lists the genes' ID.
methy	Index of M (methylated) group.
unmethy	Index of U (unmethylated) group.
percentage	A number ranges from 0 to 1 specifying the percentage of samples of group 1 and group 2 groups used to link probes to genes. Default is 0.2.
rm.probes	A vector lists the probes name.
correlation	Type of correlation to identify. Default is negative: look for hypomethylation and increase target expression.
permu.size	A number specify the times of permuation. Default is 10000.
permu.dir	A path where the output of permuation will be.
cores	A interger which defines number of core to be used in parallel process. Default is 1: don't use parallel process.

Value

Permutations

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 (creator: [e-mail]) Tiago C Silva (maintainer: [e-mail])

References

Yao, Lijing, et al. "Inferring regulatory element landscapes and transcription factor networks from cancer methylomes." Genome biology 16.1 (2015): 1.

Examples

data <- ELMER:::getdata("elmer.data.example")
permu <-get.permu(data = data,
                  geneID=rownames(getExp(data)),
                  rm.probes=c("cg00329272","cg10097755"),
                  permu.size=5)

ELMER documentation built on Nov. 8, 2020, 4:59 p.m.