ipdmr {ENmix} | R Documentation

## Differentially methylated regions

### Description

To identify differentially methylated regions using an interval P value method

### Usage

           ipdmr(data,include.all.sig.sites=TRUE,dist.cutoff=1000,bin.size=50,
                 seed=0.05,region_plot=TRUE,mht_plot=TRUE,verbose=TRUE)

### Arguments

`data` | A data frame with colname name "chr","start", "end","p" and "probe", indicating chromosome (1,2,3,...,X,Y), chromosome start and end position, P value and probe names
`include.all.sig.sites` | Whether to use CpG singletons in calculation of FDR
`dist.cutoff` | Maximum distance in base pair to combine adjacent DMRs, and the maximum distance between CpGs where auto-correlation will be calculated
`bin.size` | bin size for autocorrelation calculation
`seed` | FDR threshold for initial selection of DMR regions
`region_plot` | If TRUE, regional plots will be produced for each DMR
`mht_plot` | If TRUE, a p-value mahattan plot with marked DMRs will be produced
`verbose` | Whether to output detailed information

### Details

The input should be a data frame with column names "chr","start", "end","p" and "probe", indicating chromosome, start and end position, P value and probe name. The function will use a novel interval p value method to identify differentially methylated regions. DMR results will be stored in a file with name resu_ipdmr.csv. If plot options were selected, two figure files will be generated: mht.jpg and region_plot.pdf.

### Author(s)

Liang Niu, Zongli Xu

### References

Zongli Xu, Changchun Xie, Jack A. Taylor, Liang Niu, ipDMR: Identification of differentially methyl-ated regions with interval p-values, Bioinfomatics 2020

### Examples

    dat=simubed()
    names(dat)
    #seed=0.1 is only for demonstration purpose, it should be smaller than 0.05 or 0.01 in actual study.
    ipdmr(data=dat,seed=0.1) #seed=0.1

[Package ENmix version 1.28.8 Index]