splitDataByDensity  R Documentation 
This function splits the methylation data into regions based on the density of CpGs.
splitDataByDensity( dat, window.size = 100, by = 1, min.density = 5, gap = 10, min.cpgs = 50, max.cpgs = 2000, verbose = TRUE )
dat 
a data frame with rows as individual CpGs appearing
in all the samples. The first 4 columns should contain the information of

window.size 
this positive integer defines the size of the
sliding window in bp. Decimal values will be rounded to the nearest integer.
The value should be greater than 10. The default value is 
by 
positive integer defines by how many base pairs the
window moves at each increment. Decimal values will be rounded to the
nearest integer. The default value is 
min.density 
positive integer defines the minimum density
threshold for each window. Decimal values will be rounded to the
nearest integer. The default value is 
gap 
positive integer defining the gap width
beyond which we consider that two regions are independent.
Decimal values will be rounded to the nearest integer.
The default value is 
min.cpgs 
positive integer defining the minimum number of CpGs within a region for the algorithm to perform optimally. The default value is 50. 
max.cpgs 
positive integer defining the maximum number of CpGs within a region for the algorithm to perform optimally. The default value is 2000. 
verbose 
logical indicates if the algorithm should provide progress report information. The default value is TRUE. 
A named list
of data.frame
containing the data of each
independent region.
Audrey Lemaçon
## data(RAdat) RAdat.f < na.omit(RAdat[RAdat$Total_Counts != 0, ]) results < splitDataByDensity(dat = RAdat.f, window.size = 100, by = 1, min.density = 5, gap = 10, min.cpgs = 50, verbose = FALSE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.