Dear Luo and list,

I am successfully using GAGE and pathview for my analyses and I like the package a lot. So, thanks for developing it.  I have some points on which I would appreciate some help and/or clarification.

AVERAGE VALUE - The first time I run the analysis with GAGE, I used an identical setup parameters as the example prepared by you in the manual. I have 8 replicates per treatment and I initially used unique column names for each sample (i.e. "DIET02_1, DIET02_2, DIET02_3, etc.) as per your example with HN and DCIS. However, I have discovered (following a casual mistake) that if instead of having a unique name samples are named with the treatments they belong (i.e. "DIET02" for all 8 replicates), the subsequent gage analysis it generates one single value for that treatment. By comparing the p values of both the above cases I have found that they are identical. Am I correct to assume that in the latter case every value assigned to the treatment are an average of the replicates?

DUPLICATE PROBES - My array has got several duplicate or triplicate probes which are correctly annotated with the same KO number. How are these probes handled by the gage analysis? For example, if I have three probes for my gene X which are annotated with the same KO number, are these going to be counted 3 times into the "set size"? Or are the values for that KO number going to be merged into one?

"COMPARE" argument of "gage" function - My experiment consists of 5 treatments (x 8 replicates). None of the treatments is a proper "control". Is it correct if I use as an argument "1ongroup" choosing one of the treatment as a ref? I have also tried the "as.group" option but when I look at the results I do not get a comparison of the chosen reference with the remaining groups, but instead one single value named "exp1". I have also tried "paired" which gives completely different results.

HEATMAP OUTPUT of "esset.grp" function - Is there any quick way to generate an output heatmap (as for sigGeneSet) removing the redundant pathways identified with function "esset.grp"? At the moment I am doing this manually and plotting the results into heatmap.2 from gplot. Is this the only way?

 Any help on the above would be greatly appreciated.

Regards.
Christian De Santis







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