R CGH V: GLAD

Here we continue with the same dataset. The GLAD package has a function, as.profileCGH which can read dataframes containing columns

 LogRatio PosBase  Chromosome PosOrder

• Create such a data.frame for the first sample. PosBase corresponds to colorectal$clones.info$kb, PosOrder is the order of each probe (try to figure out how to define this one). Name the data.frame x.
• create a CGH profile from this data.frame using as.profileCGH(x)
• perform segmentation using the function glad()
• plot segmented CGH profile with plotProfile().
  • If you do data(cytoband) before your plot you can add cytobands above the plot and then it is easier to identify where the gains and losses are.
  • Or if you add the parameter Chromosome = in the function you can plot the chromosomes one by one to identify the changes.

3. Hand in your CGH profile plot and describe where you find gains and losses

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