Question: Why are gene expression phylogenies and the structure of hierarchical clustering so different?
gravatar for haoyan14ioz
3.2 years ago by
haoyan14ioz0 wrote:

Hi all, I'm a little bit confused about gene expression phylogenies and the structure of hierarchical clustering. I got two different structures from hierarchical clustering (Pearson correlation coefficient, "complete" hclust method from pheatmap package) and gene expression phylogeny(Neighbour-joining trees based on pairwise distance matrices(1-r, r is Spearman's correlation coefficient)) using the same expression data, and the details are in the attachment. And the topology from hierarchical clustering seemed more consistent with species tree. What does anybody think about that? Why does the different topologies happen to this? Which one is better to explain phylogeny relatedness?

hierarchical clustering:

gene expression phylogeny:

Any help will be highly appreciated.


rna-seq • 1.0k views
ADD COMMENTlink written 3.2 years ago by haoyan14ioz0

Different methods produce different outputs. There's nothing surprising here.
Complete linkage = furthest neighbour joining
Spearman's correlation != Pearson's correlation
EDIT: To clarify, the two approaches described are both hierarchical clustering using different distance measures and different linkage.
I don't see where there's any phylogeny involved here.

ADD REPLYlink modified 3.2 years ago • written 3.2 years ago by Jean-Karim Heriche23k

Thank you so much, Jean-Karim. I'm sorry, I forgot the species tree. I see the methods between spearman's correlation and pearson's correlation are different. But the very huge different topology, I can't understand, because they are both correlation after all. PS: I don't find spearman's correlation in pheatmap package in R. Which method is more suitable to analysis expression phylogeny, what do you think?

ADD REPLYlink written 3.2 years ago by haoyan14ioz0
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