I have a bunch of clusters that I made using affinity propagation on the Gene Expression dataset , so I have bunch of clusters on the Autism and bunch of clusters on the Control. Also we know that there are well known Autism genes that people have combined at SFARI genes database. So My question is that what kind of analysis I can draw based on those groups of clusters across autistic and control patients, how can I use the well known autistic genes database and how can different datasets with same technique for example if I have another Gene Expression dataset then what can I do?
I need the suggestions of someone is well aware of this problem , In my understanding I could do Gene Set Enrichment analysis of clusters but then how can I filter or prune those clusters based on GESA?
Regards
What is the scientific question? I hope you do not try to find the cause of autism based on some RNA-seq but have a more elaborate (and specific) topic you are working on.
I am analyzing the clusters formed in both the groups, My aim is to report the dynamics of the clusters that are formed in two groups, for example I am interested 1) is there some significant difference between the number of clusters between the two communities (using Affinity propagation since in this techniques clusters are formed automatically) 2) I need to study the clusters that are formed in each group and after pruning them using some reprocessing steps like enrichment analysis , I need to analyze the evolution of communities/clusters across two groups that is either communities are increasing in size , decreasing , getting fused etc. 3) Then I need to find DEGs(Differentially Expressed Genes across 4 or 5 datasets and clusters those DEGs and study their evolution across datasets. So you can say my main problem is to analyze the clusters formation between subjects and controls. If you think that this is something that is not useful, utter nonsense ,need more elaboration or consideration or not clear then you can suggest me .
Regards