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interpreting GeneNet data

Hello All, I have a microarray gene expression data with 126 genes and 45 samples (GSMs). My aim is to find whether these genes are related/dependent on each other. it seems these genes are not directly correlated as is inferred from simple correlation (cor) and partial correlation (ppcor) methods. With 'GeneNet' from R I obtained results with few genes directly correlated. [ used "dynamic, with shrinkage" method for ggm.estimate.pcor.] Since my data does not have time point intervals, I guess dynamic one should not be used. my question is which method (static or dynamics with/out shrinkage) should I use?. Also an interpretation of statistics data (where density distribution function, type of statistics are given) will be really helpful.

Thanks in advance for your help- Simanti

correlation kappa eta0

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