Clustering of samples based on gene expression

Question

[shivangi.agarwal800]

Hi Guys,

I need to cluster some samples A,B,C based on the gene expression (Please see the data below). I made a matrix of 1s and 0s where 1 indicate gene is present and zero indicates its absence. While I am clustering them using Hierarchical clustering (HC) method, samples A and C are clustered closely. But, as we can see, samples A and B share 2 genes in common. I understand how the HC algorithm is working. It is clustering based on both 1s and 0s. But, is there any other method we can apply to cluster samples A and B closely, (like avoiding zeros and clustering based on only 1s) ?

Sample    GeneA    GeneB    GeneC    GeneD    GeneE    GeneF    GeneG    GeneH    GeneI    GeneJ    GeneK    GeneL    GeneM    GeneN    GeneO    GeneP    GeneQ
A         0        0        0        0        0        0        0        0        0        0        0        0        0        0        1        1        0
B         1        1        1        1        1        1        1        1        1        1        1        1        1        1        1        1        1
C         0        0        0        0        0        0        0        0        0        0        0        0        0        0        0        0        0

Thanks in advance

[Pappu]

You can use pheatmap to cluster it.

[Ram]

That's a visualization tool that internally uses hclust. Any change that can be done in pheatmap's clustering methods can be done without involving pheatmap as well. There is no reason to involve pheatmap here.