First I just want to say thanks for all the help I've had from the list so far..)
I now have what I think is a clustering problem. I have lots of objects which I have measured a dissimilarity between. Now, this list only has one entry per pair, so it is not symmetrical. Example input: NameA NameB Dist 189_1C2 189_1C1 0 189_1C3 189_1C1 0.017 189_1C3 189_1C2 0.017 189_1C4 189_1C1 0 189_1C4 189_1C2 0 189_1C4 189_1C3 0.017 189_1C5 189_1C1 0.05 189_1C5 189_1C2 0.05 189_1C5 189_1C3 0.067 189_1C5 189_1C4 0.05 189_1C6 189_1C1 0.05 189_1C6 189_1C2 0.05 189_1C6 189_1C3 0.067 189_1C6 189_1C4 0.05 189_1C6 189_1C5 0 The distance measure is 0 if identical, and then increases with increasing dissimilarity up till 1. What I would like to get from these data is a hierarchical clustering graph. In this example I would then group 189_1C2 189_1C1 189_1C4, 189_1C6 189_1C5, and 189_1C3 off with itself. The distances between the groups should be the mean distances between the objects within each group (I think). I have looked at hclust and it seems like it should be able to do what I want. However, I am unsure of how to use it to get what I am looking for. Thankyou in advance for your help! Karin -- Karin Lagesen, PhD student [EMAIL PROTECTED] http://folk.uio.no/karinlag ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
