consolidateDMRs: Consolidating Differentially Methylated Regions (DMRs)
In kamalfartiyal84/methylPipe: Base resolution DNA methylation data analysis

Description Usage Arguments Details Value Author(s) See Also Examples

Joins differentially methylated regions according to their proximity to each other, statistical significance and methylation difference

1	consolidateDMRs(DmrGR, pvThr=0.05, MethDiff_Thr=NULL, log2Er_Thr =NULL, GAP=0, type=NULL, correct=FALSE)

`DmrGR`	the GRanges object resulting from the `findDMR` function
`pvThr`	numeric; the minimum pvalue for a DMR to be selected
`MethDiff_Thr`	numeric; the absolute value of minimum methylation difference percentage (for both hyper- and hypo-methyaltion) cutoff for the selection of a DMR
`log2Er_Thr`	numeric; the absolute value of minimum log2Enrichment (for both hyper- and hypo-methyaltion) cutoff for the selection of a DMR
`GAP`	numeric; the minimum distance between two adjacent DMRs; DMRs closer than that will be joined, resulting DMRs will be updated mean methylation difference and Pvalues combined using the Fisher's Method
`type`	character; one of the "hyper" or "hypo", specifies the type of differentially menthylated regions selected
`correct`	logical; whether to correct the pvalues using the Benjamini-Hochberg muliple testing correction method

After the DMRs are identified by findDMR method, a consolidation can be applied on them. This functions allows to select hyper/hypo differentially methylated regions based on P-value and absolute methylation change thresholds. Moreover, DMRs closer than a given distance can be joined. The final GRanges object with the set of final DMRs will be provided with updated mean methylation difference and Pvalues combined using the Fisher's Method.

Either NULL or a GRanges object containing the differential methylated regions satisfying the criteria.

Kamal Kishore

findDMR

DMRs_file <- system.file('extdata', 'DMRs.Rdata', package='methylPipe')
load(DMRs_file)
hyper.DMRs.conso <- consolidateDMRs(DmrGR=DMRs, pvThr=0.05, GAP=100, type="hyper", correct=TRUE)
hyper.DMRs.conso