MBDDiff: Performing differential methylation analysis based on...
In Liuy12/MBDDiff: MBDDiff for processing MBDcap-seq datasets

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

This function is basically a wrapper function for XBSeq

1	MBDDiff(promoter, background, conditions, method = "pooled", sharingMode = "maximum", fitType = "local", pvals_only = FALSE, paraMethod = "NP")

`promoter`	A data.frame or matrix that contains promoter methylation levels
`background`	A data.frame or matrix of the same dimension as promoter that contains background noise for each promoter region
`conditions`	A character or factor vector that contains the experimental design information
`method`	Method used to estimate SCV
`sharingMode`	Mode of sharing of information
`fitType`	Option to fit mean-SCV relation
`pvals_only`	Logical; Specify whether to extract pvalues only
`paraMethod`	Method to use for estimation of distribution parameters, 'NP' or 'MLE'

For further details please refer to XBSeq

A list of two elements:

MBD

A XBSeqDataSet object

A data.frame of the following elements:

`id`	rownames of XBSeqDataSet
`baseMean`	The basemean for all promoters
`baseMeanA`	The basemean for condition 'A'
`baseMeanB`	The basemean for condition 'B'
`foldChange`	The fold change compare condition 'B' to 'A'
`log2FoldChange`	The log2 fold change
`pval`	The p value for all promoters
`padj`	The adjusted p value for all promoters

Yuanhang Liu

https://github.com/Liuy12/MBDDiff

estimateRealCount, XBSeqDataSet, estimateSCV, XBSeqTest

  ## Not run: 
    data(PromoterCount)
    conditions <- c(rep('C1', 3), rep('C2', 3))
    MBDDiff(Promoter, Background, conditions)
    
## End(Not run)