Dear Steve, Just for the record, I think I have found a function that allows drawing of a dendrogram with the leaf order specified. It is draw.dendrogram {NeatMap}. I cannot see a way of directly drawing the reordered dendrogram in the heatmap, though, so I still think that your solution is better :-) Gavin. On 28 May 2011 19:53, Gavin Koh <gavin.koh at="" gmail.com=""> wrote: > Dear Steve, > > Yes, I expect that in preserving the order in which I have the sample > currently, the branches will cross. > You are right: it will be clearer to cluster by k-means then use > ColSideColors to colour the leaves than to try to draw a dendrogram > with criss-crossing branches. Thanks for helping me thinking this > through. > > Gavin. > > On 28 May 2011 18:20, Steve Lianoglou <mailinglist.honeypot at="" gmail.com=""> wrote: >> Hi Gavin, >> >> On Sat, May 28, 2011 at 11:06 AM, Gavin Koh <gavin.koh at="" gmail.com=""> wrote: >>> Dear Steve, I have healthy controls and patients, so two groups. >>> k-means misclassifies a few study subjects, but by and large, >>> redrawing the dendrogram while preserving the ordering is not going to >>> serious mess things up. >> >> Sorry if my post came across in the wrong way -- I'm not trying to >> imply that you are trying to show something that isn't true, or >> something ... I'm actually not sure how you interpreted my email, >> because I'm not sure what you're trying to say in your reply, so let >> my try another way :-) >> >> I guess my point is that: yes, you have two groups when you condition >> group assignment based on a state we call "healthy" and "affected" (or >> whatever you call them here). >> >> If you are asking to group your patients in a different way -- this >> time using your gene expression profiles -- it's not totally unusual >> for things to change a bit. >> >> So, again, I'm not trying to lecture here, but this is the way I >> understand it. If I'm wrong, feel free to correct me: >> >> The distances we "walk along" the arms/branches of the dendrogram say >> something about the distance between the "things" they are connecting. >> If you didn't change any params in your heatmap call, the default >> distance measure between your vectors is calculated by its euclidean >> distance, and that just is what it is. The dendrogram is then drawn to >> respect those distances. If you move things around, then you are >> saying something different about those distances, right? >> >> In this context, I'm confused about your point when you say "redrawing >> the dendrogram while preserving the ordering is not going to serious >> mess things up" -- what ordering do you expect to be preserved ... is >> it the columns of the matrix that you passed in? If you don't want to >> move those columns around, then ?do you want the branches of the tree >> to criss-cross or something? >> >> The way I see it, you are kind of stuck if you intend to draw a >> dendrogram at all. >> >> So -- how can we move things around in a natural way? >> >> Maybe you can choose a different distance measure? >> Maybe you can normalize your data in a different way? >> Maybe you can plot a subset of genes -- maybe those with the highest >> variance across all your data, which might result in new distances >> calculated, and a different drawing of the branches on the tree. >> >> You could always pass in your own dendrogram structure to the heatmap >> and "arbitrarily" calculate distances so that the tree ?draws as you >> want, but I don't think that's something you'd want to do anyway. >> >> Another approach to show "likeness" between expression profiles is to >> not focus on the dendrogram lining up "just so", but to rather add a >> list of colors to the examples (columns) of your data by using the >> "ColSideColors" parameter. Say the first 10 columns of your matrix are >> from the 10 controls, and the last 10 are from the affecteds. You can >> do: >> >> R> heatmap.2(my.data, ..., ColSideColColors=c(rep('blue', 10), rep('red', 10))) >> >> If, as you say, the expression profiles are *mostly* similar, you'll >> see that, by and large, the blue experiments will be "chunked" w/ >> blue, and the red expts are chunked with the red, which might show the >> same point you're trying to make with the dendrogram. >> >> HTH, >> -steve >> >> -- >> Steve Lianoglou >> Graduate Student: Computational Systems Biology >> ?| Memorial Sloan-Kettering Cancer Center >> ?| Weill Medical College of Cornell University >> Contact Info: http://cbio.mskcc.org/~lianos/contact >> > > > > -- > Hofstadter's Law: It always takes longer than you expect, even when > you take into account Hofstadter's Law. > ?Douglas Hofstadter (in G?del, Escher, Bach, 1979) > -- Hofstadter's Law: It always takes longer than you expect, even when you take into account Hofstadter's Law. ?Douglas Hofstadter (in G?del, Escher, Bach, 1979)