What is the best clustring method for gene expression base on logFC

Question

[Calangoa]

Hello there, I have a small number of genes (about 40) containing there expression base on log transformation of fold change and their p.value for 12 individual microarray dataset. I decided to find co expression genes and cluster them to find similar datasets and co-expression. What clustering method is good for this data? previusly I wanted to do WGCNA but it is for a huge number of gene, then I decided to do heirecichal clustring but after reading different paper about clustring I found my self inexpert . what clustering method (average linkage, centeroid, complete, single linkage)and distance measurment (peardon, euclidean, manhattan,..)is better for my data?

I appreciate if anyone could help me.

Answer 1

[ishackm]

Hi Nafas,

For your data, I would recommend using hierarchical clustering (Dendrogram) to visually see the expression of the 40 genes between your samples, I would use the complete clustering method and the Euclidean measuring distance.

[Calangoa]

Many Thanks ishackm.