segmentData {CGHcall} | R Documentation |
A wrapper function to run existing breakpoint detection algorithms on arrayCGH data. Currently only DNAcopy is implemented.
segmentData(input, type = "dataframe", method = "DNAcopy", ...)
input |
Either the name of a file or a dataframe. See details for the format. |
type |
What kind of data format is used as input? Either 'dataframe' or 'file'. |
method |
The method to be used for breakpoint detection. Currently only 'DNAcopy' is supported, which will run the segment function. |
... |
Arguments for segment . |
The input should be either a dataframe or a tabseparated textfile (textfiles must contain a header). The first three columns should contain the name, chromosome and position in bp for each array target respectively. The chromosome and position column must contain numbers only. Following these is a column with normalized log2 ratios for each of your samples. If the input type is a textfile, missing values should be represented as 'NA' or an empty field.
This function returns a dataframe in the same format as the input with segmented arrayCGH data.
Sjoerd Vosse & Mark van de Wiel
Venkatraman, A.S., Olshen, A.B. (2007). A faster circulary binary segmentation algorithm for the analysis of array CGH data. Bioinformatics, 23, 657-663.
data(Wilting) ## First preprocess the data raw.data <- preprocess(Wilting, type="dataframe") ## Simple global median normalization for samples with 75% tumor cells perc.tumor <- rep(0.75, 3) normalized.data <- normalize(raw.data, cellularity=perc.tumor) ## Segmentation with slightly relaxed significance level to accept change-points. ## Note that segmentation can take a long time. ## Not run: segmented.data <- segmentData(normalized.data, alpha=0.02)