Hi,
I am an old-fashioned biologist with a gene of interest. After learning how to download and play with TCGA data, i found that expression of my gene-of-interest correlates with expression of several genes that belong to a specific pathway. It fits my hypothesis that upregulation of my gene-of-interest would cause (or at least be associated with) upregulation of those other genes. But is there anything I can do now informatically?
I would be interested to know if i can identify a subgroup of patients in the TCGA dataset that have high expression of my gene and its individual correlates (or a subgroup that has low expression of my gene of interest and its correlates). Can anybody suggest a way to do that? Or a paper I can read?
thanks in advance. confused (but evolving) biologist
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Is Factor Analysis a good option for this?
Have you done this initial analysis for a single sample (or more than one)?
There are several portals that allow access to TCGA data over the web. Examples are http://www.cbioportal.org/ https://dcc.icgc.org/ and http://www.oncolnc.org/. You could start identifying samples that interest you using the portals.
Hi,
thank you for your reply. I have done this initial analysis in the TCGA BRCA provisional dataset (the one with 1105 patient samples). I used linear regression and found that my expression of my gene of interest was predictive of expression of several different genes which belong to MAPK pathways.
i used the cbioportal to download the dataset, and I see that i can pick high or low expressors of my gene of interest. But what is the appropriate statistical test after that?
If i separate out say the highest and lowest quartiles of my gene of interest, should I then do T-tests to prove that they have differential expression of MAPK genes? I know how to do that individually, but is there a way to do that for all the genes? and is there a way to come up with some kind of score for MAPK pathway upregulation so that I can test whether that score explains how my gene of interest affects survival?
thanks for your time.