plotSegmentation {Vega} | R Documentation |
This function allows to plot the observed data superimposing the respective segmentation. By the parameter 'opt' he user can plot the LRR mean values of each segment or the computed aberration kind. In plot window the gain and the loss are identified by a line having value of 1 and -1 respectively.
plotSegmentation(CNVdata, segmentation, chromosomes, opt = 0)
CNVdata |
The data matrix. |
segmentation |
The computed segmentation. |
chromosomes |
The chromosomes that have to be plotted. |
opt |
If opt=0 (default) then the LRR mean values are plotted, if opt=1 the computed labels are plotted. |
If the argument opt=1 then gains and losses are identified by 1 and -1 respectively.
Sandro Morganella, Luigi Cerulo, Giuseppe Viglietto, Michele Ceccarelli Maintainer: Sandro Morganella <morganellaalx@gmail.com>
Morganella S. et al. (2010). VEGA: Variational segmentation for copy number detection, Bioinformatics.
# Import the data data(G519) # Compute the segmentation for all chromosomes seg <- vega(G519, c(1:22, "X", "Y")) # Plot the results for all chromosomes in terms of mean of LRRs plotSegmentation(G519, seg, c(1:22, "X", "Y"), opt=0) # Plot the results for all chromosomes in terms of aberration kinds plotSegmentation(G519, seg, c(1:22, "X", "Y"), opt=1)