i have used affymetrix data with diseased samples of TB and have done genespring analysis..further i have found the semantic similarity and dn have done clusterone analysis..as im doing a small prject form my final yr..i need to reduce the no of genes and find more specific target genes.How can i proceed further for this?
hii everyone i hav been doing a small work to find DE genes using network analysis..presently i have used cytoscape clusterone plugin and have got a cluster of almost 15 genes..what can i do further to get more specific genes and how? i would be glad if someone helped me out
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What type of data are you using?
How many replicates do you have?
Edit: Maybe Im missing something here but to me differential expression analysis and network analysis are 2 seperate types of analysis. I would have thought that you would run differential analysis first and then a network analysis as a way of further analysing differentially expressed genes. So finding "DE genes using network analysis" makes no sense to me.
Please define what you mean by "more specific genes" properly.
A list of 15 genes is quite small, I would think that should be specific enough. But as @kennethcondon2007 has said we will need a lot more information before we can provide any further help. First, what is your threshold for a differentially expressed gene? Second, how did you calculate semantic similarity? Third, how much farther do you need to reduce your gene set, to 10, 5, 1?
the threshold value i hav set is 2.5 i hav used the funsimmat database to find the semantic similarity with GO terms I wanted to reduce the geneset atleast to 10
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Where do the interactions come from? You have identified differentially expressed genes, which would give you a set of nodes in Cytoscape. But where did the edges come from that you ran clustering on? And most important of all, what is the actual problem you are trying to solve by performing a network analysis?