prepSC: Process single-cell data

In rhondabacher/methylscaper: Visualization of Methylation Data

Process single-cell data

Description

This function subsets the data and prepares it for visualizing by generating representation methylation-state matrices from single-cell methylation data (for example, sc-MNT data). We assume the data has already been preprocess using the subsetSC function in methylscaper. See the vignette for a more thorough explanation of each parameter. The output should be passed directly to the plotting function.

Usage

prepSC(dataIn, startPos = NULL, endPos = NULL, updateProgress = NULL)

Arguments

dataIn	A list object containing two elements labelled gch and hcg (already pre-processed.)
startPos	The index of the first position to include in the visualization. If using this within the R console it is recomended to specify the start and end directly. In the Shiny app, a slider will let the user refine these positions.
endPos	The index of the final position to include in the visualization.
updateProgress	A function for generating progress bars in the Shiny app. Should be left NULL otherwise.

Value

The output is a list containing the elements 'gch' and 'hcg. Each is a dataframe with reads/cells on the rows and each column is a base-pair. The matrix is coded as follows: -2: unmethylated GCH or HCG site -1: base pairs between two unmethylated GCH or HCG sites 0: base pairs between mismatching methylation states of two GCH or HCG sites 1: base pairs between two methylated GCH or HCG sites 2: methylated GCH or HCG site

Examples

 
data(singlecell_subset)
prepsc.out <- prepSC(singlecell_subset, 
                 startPos = 105636488, endPos = 105636993)

rhondabacher/methylscaper documentation built on April 18, 2023, 1:47 p.m.