ipdmr | R Documentation |
To identify differentially methylated regions using an interval P value method
ipdmr(data,include.all.sig.sites=TRUE,dist.cutoff=1000,bin.size=50,
seed=0.05,region_plot=TRUE,mht_plot=TRUE,verbose=TRUE)
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 |
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.
Liang Niu, Zongli Xu
Zongli Xu, Changchun Xie, Jack A. Taylor, Liang Niu, ipDMR: Identification of differentially methyl-ated regions with interval p-values, Bioinfomatics 2020
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
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