The methods used for the processign of the date should be mentioned in the Methods section of the paper the data come from (here it is Richardson AL, Wang ZC, De Nicolo A, Lu X et al. X chromosomal abnormalities in basal-like human breast cancer. Cancer Cell 2006 Feb;9(2):121-32. PMID: 16473279). I quote from the paper:
"RNA extraction, cRNA synthesis, and hybridization to Affymetrix Human Genome U133 Plus 2.0 Arrays were performed as described previously (Signoretti et al., 2002 and Wang et al., 2004). Raw expression data obtained using Affymetrix GENECHIP software was normalized and analyzed using DNA-Chip Analyzer (dChip) custom software (W.H. Wong and C. Li, http://www.dChip.org/). Array probe data were normalized to the mean expression level of each probe across a sample set. Where indicated, tumors were classified as BLC or non-BLC on the basis of their expression array characteristics, using dChip hierarchical clustering analysis as previously described (Matros et al., 2005 and Wang et al., 2004). Comparisons between results obtained on BLC or BRCA1 tumors, non-BLC tumors, and normal breast samples were performed using the dChip “Compare Sample” function. A threshold of 1.2-fold overexpression in BLC and BRCA1 tumors was applied with 90% confidence. Of 1271 gene probes that map to the X chromosome, 60 satisfied these overexpression criteria with a range of fold difference from 1.35 to 5.11. The false discovery rate (number) of 1000 permutations was as follows: median, 0% (0); 90th percentile, 3.3% (2). Of the 60 probes, 19 were redundant (two or more probes mapping to the same gene) and excluded, leaving 41 gene-specific probes for use in the expression plot of Figure 5B. The complete gene expression array data set is available on the NCBI GEO database (accession no. GSE3744)."
Since this is a standard Affymetrix human genome chip, it's CDF should either be embedded in most packages used to analyse this kind of data (limma is an industry gold standard example ;-), or downloaded from the Afymetrix website. Please note that the CDF itself may be quite old and it's annotation not always accurate any more (I have no experience with human data), so it's worth using an updated CDF (see Dai et al 2005).