Question: Can anyone introduce me a free tool for finding upstream regulators of differentially expressed genes?
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gravatar for Sib
7 weeks ago by
Sib20
Sib20 wrote:

I performed a differential expression analysis of microarray and RNAseq datasets between healthy control samples and patient samples and obtained a list of differentially expressed genes. Now, I want to find upstream regulators of these DEGs. I am seeking a tool or platform that does this for free. Can anyone help me?

ADD COMMENTlink written 7 weeks ago by Sib20
1

You can do a lot of things for free at a basic level of bioinformatics. What kind of regulator are you looking for? Would you please provide more details and try to clarify what you need exactly?

ADD REPLYlink written 7 weeks ago by Hamid Ghaedi710

Thanks for your answer. We want to introduce new blood candidate biomarkers for one disease. We hypothesize that novel and potentially more specific biomarkers in the blood could be identified by searching for disease-associated pathways that overlap between cells in the peripheral blood and the inflamed main organ involved in that disease. So we want to perform a differential expression analysis between healthy control datasets and Inflamed organ datasets. We will obtain a list of DEGs by this step. And we want to perform differential expression analysis between blood datasets of patients and blood datasets of healthy people and obtain another list of DEGs. Then we wish to find common DEGs between these two DEG lists and introduce candidate blood biomarkers. Similarly, we want to obtain upstream regulators of DEGs of inflamed organ and find common genes between these regulators and DEGs of blood and introduce these GEGs as candidate biomarkers. An article had done this by IPA. But we could not use that and we are seeking a free platform or an integrated bioinformatics method to do the purpose like IPA

ADD REPLYlink modified 7 weeks ago • written 7 weeks ago by Sib20
1

No idea about your hypothesis, but for finding interaction between genes you may want to try to make an expression network with a package like WGCNA in R. This would help you to make a network for interacting genes in your dataset. BUT it is not going to be one step analysis, and several preprocessing steps should be undertaken. Here are some posts from Biostar you may want to consider:

1- Question: Network analysis of genes using R

2- Question: Construct gene coexpression network

3- Question: Gene network with expression data

4- Question: Weighted Gene Expression Network

5- Question: Differential Coexpression Analysis

ADD REPLYlink modified 7 weeks ago • written 7 weeks ago by Hamid Ghaedi710
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