Hello Everyone,
I am recently working on gene co expression modules of a disease. We selected gene A and done its positive correlation analysis at 50%, resulted in top 100 genes were correlated with gene A. we find many genes which are relevant to disease on which we are working on. Now we think that that When gene A is over expressed one gene among its top 100 correlated gene is also over expressed which we think might be a prime cause of the disease, but I am unable to find the way to validate such phenomena!! Can any one guide me how to do this? Thanks and Regards
have you found what exactly gene B is ? if that is the case, things would be rather straightforward, try to associate gene B with the disease with possible explanations you can get(possibly by literature mining first), genetic, epigenetic, expression regulation, etc. then design a validation experiment for that specific mechanism.
If what you are trying to validate is that one gene(gene B in your case) is co expressed with another gene(gene A) . you may enlarge your sample size to enhance your confidence on the co expression pattern. or try to see if there are public data in geo which can be used to validate your result.( the character, tissue, age, etc, of the validation data and your data should match as coexpression pattern may change in different tissues )
have you found what exactly gene B is ? if that is the case, things would be rather straightforward, try to associate gene B with the disease with possible explanations you can get(possibly by literature mining first), genetic, epigenetic, expression regulation, etc. then design a validation experiment for that specific mechanism.
If what you are trying to validate is that one gene(gene B in your case) is co expressed with another gene(gene A) . you may enlarge your sample size to enhance your confidence on the co expression pattern. or try to see if there are public data in geo which can be used to validate your result.( the character, tissue, age, etc, of the validation data and your data should match as coexpression pattern may change in different tissues )
I may not be a good person to comment here, but just sharing my thoughts. If the over expression of gene B with the over expression of A is observed in a diseased system, why don't you do the over expression of gene A in a normal system? If gene B is not getting over expressed in a normal system, isn't that a proof?
Dear Ayaz
You intend to observe the expression patterns as you mentioned. But please ask yourself what would be your priorities:
1. Analysing coexpressed genes base don significant correlation
2. How many of these genes are "differentially" expressed genes?
Then you may apply GWAS studies base don the patterns.
Whether or not you would like to explicitly rank the genes that are associated depends on what kind of expression networks you would like to see. You may then rank based on
1. Genes X diseased networks ( Diseasome patterns)
2. Physical interaction involving expression or mere associations
3. Epigenetic factors and tissue specificty.
I hope this helps
Prash
In my opinion the protein pool down assay by designing antibody for gene A may help to find out whether the gene B is also directly correlated or not. Yeast two hybrid method can also be used for checking out the interaction. Sometimes the spatiotemporal expression of two unrelated genes matches so nicely that at the time of expression of one gene other also expresses and they may not be in a direct correlation. Or the gene x may be affecting gene B through a wide but strong network........hence a wet lab experiment involving the genes under consideration will provide a clue ...
True to a certain extent, Sunil.
It proves to be expensive right from raising an Ab to confirming the correlation. The bioinformatics analyses can provide some statistics relative to this in lessening the scale of experimentation, time and energy.
Dear Prashanth Suravajhala
you are absolutely right
but according to question he has shortened to a point to gene A and Gene B and hence my suggestion was.......until you verify its a hypothesis which may go right or wrong
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