Confusion related to gene expression

Question

I have a set of gene expression data downloaded from http://www.ncbi.nlm.nih.gov/geo. I have two sets of data, one is the raw probe intensity data set in the form of CEL files. Another is processed txt file.

Here is a link for example http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7904

I don't know what kind of processing is done to generate the processed data from the raw CEL files. For example in the above link, I have processed data like

SOFT formatted family file(s) MINiML formatted family file(s) Series Matrix File(s)

I don't know what sort of processing is done to generate those files. Any suggestions? I can read the raw CEL files in matlab but what sort of preprocessing am I supposed to do?

I also want to map these probe its to gene ids and get the corresponding gene. How can I accomplish this? I know matlab. But I am bit confused about the terminology and all. Any suggestions?

Answer 1

If you click through to some of the samples in the study, eg. GSM194397, GSM194398, etc. it mentions under the "Data processing" section that "The data were analyzed with dchip with default normalization settings".

You can learn more about dChip over at the dChip website.

Answer 2

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).