multipcf(data, pos.unit = "bp", arms = NULL, Y = NULL, gamma = 40,
normalize=TRUE, w=1, fast = TRUE, assembly = "hg19", digits = 4,
return.est = FALSE, save.res = FALSE, file.names = NULL, verbose
= TRUE)
data
. If not specified chromosome arms are found using the built-in genome assembly version determined by assembly
.data
contains Winsorized values. If provided, these values are used to calculate the mean of each segment, otherwise the copy number values in data
are used. Y
must be on the same form as data
.save.res = TRUE
.return.est = TRUE
a list with the following components:return.est = FALSE
only the data frame containing the segments is returned.
If save.res = TRUE
the results are also saved in text files with names as specified in file.names
. If file.names=NULL
, a folder named "multipcf_results" is created in the working directory, and the segments and copy number estimates are saved in this folder as tab-separated files named segments.txt and estimates.txt, respectively.imputeMissing
, pcf
#Load lymphoma data:
data(lymphoma)
#Take out a subset of 3 biopsies from the first patient (using subsetData):
sub.lymphoma <- subsetData(lymphoma,sample=1:3)
#Check for missing values in data:
any(is.na(sub.lymphoma))
#FALSE
#First winsorize data to handle outliers:
wins.lymph <- winsorize(sub.lymphoma)
#Run multipcf on subset lymphoma data (using a low gamma because of low-density data)
multi.segments <- multipcf(data=wins.lymph,gamma=12,Y=sub.lymphoma)
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