epigraHMMDataSetFromMatrix: Create a epigraHMMDataSet from matrices of counts

In plbaldoni/epigraHMM: Epigenomic R-based analysis with hidden Markov models

Create a epigraHMMDataSet from matrices of counts

Description

This function creates a RangedSummarizedExperiment object from matrices of counts. It is used to store the input data, the model offsets, and the results from the peak calling algorithms.

Usage

epigraHMMDataSetFromMatrix(countData, colData, rowRanges = NULL)

Arguments

countData	a matrix (or a list of matrices). If countData is a list of matrices, matrices must be named, have the same dimensions, and, at least, a matrix with name 'counts' must exist (see details).
colData	a data.frame with columns condition and replicate. condition refers to the experimental condition identifier (e.g. cell line name). replicate refers to the replicate identification number (unique for each condition).
rowRanges	an optional GRanges object with the genomic coordinates of the countData

Details

Additional columns included in the colData input will be passed to the resulting epigraHMMDataSet assay and can be acessed via colData() function.

Value

An epigraHMMDataSet object with sorted colData regarding conditions and replicates. Experimental counts will be stored in the 'counts' assay in the resulting epigraHMMDataSet object. If ‘countData' is a list of matrices, the resulting ’counts' assay will be equal to ‘countData[[’counts']]'.

Additional matrices can be included in the epigraHMMDataSet. For example, if one wants to include counts from an input control experiment from ‘countData[[’controls']]‘, an assay ’control' will be added to the resulting epigraHMMDataSet..

Author(s)

Pedro L. Baldoni, [e-mail]

References

https://github.com/plbaldoni/epigraHMM

Examples

countData <- list('counts' = matrix(rpois(4e5,10),ncol = 4),
'controls' = matrix(rpois(4e5,5),ncol = 4))
colData <- data.frame(condition = c('A','A','B','B'), replicate = c(1,2,1,2))
object <- epigraHMMDataSetFromMatrix(countData,colData)

plbaldoni/epigraHMM documentation built on Oct. 15, 2023, 7:53 p.m.