normalize read coverage between samples
The function normalizes coverage values between samples using a scaling factor derived from differences between mean or median of coverage distributions
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normalizeCoverage(obj,method="median",chunk.size,save.db,...) ## S4 method for signature 'methylRawList' normalizeCoverage(obj, method = "median", chunk.size = 1e+06, save.db = FALSE, ...) ## S4 method for signature 'methylRawListDB' normalizeCoverage(obj, method = "median", chunk.size = 1e+06, save.db = TRUE, ...)
a string "mean" or "median" which denotes median or mean should be used to calculate scaling factor. (Default:median)
Number of rows to be taken as a chunk for processing
A Logical to decide whether the resulting object should be saved as flat file database or not, default: explained in Details sections
optional Arguments used when save.db is TRUE
depending on class of input object
chunk.size is only used when working with
as they are read in chunk by chunk to enable processing large-sized
objects which are stored as flat file database.
Per default the chunk.size is set to 1M rows, which should work for
most systems. If you encounter memory problems or
have a high amount of memory available feel free to adjust the
save.db is per default TRUE for methylDB objects as
while being per default FALSE for
methylRawList. If you wish to
save the result of an
in-memory-calculation as flat file database or if the size of the
database allows the calculation in-memory,
then you might want to change the value of this parameter.
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