View source: R/DNAcopyMethods.R
CNA | R Documentation |
Creates a ‘copy number array’ data object used for DNA copy number analyses by programs such as circular binary segmentation (CBS).
CNA(genomdat, chrom, maploc, data.type=c("logratio","binary"),
sampleid=NULL, presorted = FALSE)
## S3 method for class 'CNA'
print(x, ...)
genomdat |
a vector or matrix of data from array-CGH, ROMA, or other copy number experiments. If it is a matrix the rows correspond to the markers and the columns to the samples. |
chrom |
the chromosomes (or other group identifier) from which the markers came. Vector of length same as the number of rows of genomdat. If one wants the chromosomes to be ordered in the natural order, this variable should be numeric or ordered category. |
maploc |
the locations of marker on the genome. Vector of length same as the number of rows of genomdat. This has to be numeric. |
data.type |
logratio (aCGH, ROMA, etc.) or binary (LOH). |
sampleid |
sample identifier. If missing the samples are named by prefixing "Sample" to consecutive integers. |
presorted |
logical indicator telling if the data have already been sorted by chrom and maploc. Default is FALSE. |
x |
object returned by CNA |
... |
arguments to be passed onto print command called within. |
Data that are NA, Inf, NaN will be removed on a per sample basis for "genomdat" and all samples for "chrom" and "maploc".
If the chrom variable has non-numeric values make it into an ordered
variable to get them ordered correctly. E.g. for human genome use:
chrom <- ordered(chrom, levels=c(1:22,"X","Y"))
to prepare the
variable if chromosomes X and Y are present in your data.
An object of class CNA
. There is a print
method that
gives the number of samples and probes and the type of data.
data(coriell)
#Combine into one CNA object to prepare for analysis on Chromosomes 1-23
CNA.object <- CNA(cbind(coriell$Coriell.05296,coriell$Coriell.13330),
coriell$Chromosome,coriell$Position,
data.type="logratio",sampleid=c("c05296","c13330"))
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