Hi everyone, Thanks everyone for the feedback! Roi, you understand correctly! I tried your suggestion and works! Cheers! Emmanuel, thank for sharing your code! It was a very didactic example. Today I didn't have headache(s) with R, only happiness, and I think this group contributed for that! :) Liam, Thanks a lot for your explanation. It's so helpful! Also thank for the blog, help me a lot! :)
Thanks everyone for helping me! It was a nice and inspiring experience for me :) Best Regards, Alina Em sex, 25 de jan de 2019 às 17:55, Liam Revell <liam.rev...@umb.edu> escreveu: > Hi Alina. > > Since you mentioned some functions of phytools, I thought it might be > helpful to describe what each function is actually doing: > > 1) The function ls.consensus computes a least-squares (LS) consensus > tree. This is the LS tree on the average patristic distance matrix of > the input trees, as described by Lapointe & Cucumel (1997). This is a > consensus method, but it has been criticized for not possessing what I > believe is referred to as the 'Pareto' property - meaning, in this case, > that the consensus tree can include relationships not present in any > input tree! (In practice, this is probably rare for real empirical > distributions of trees.) In general, the resultant tree will usually be > completely resolved and if all input trees are ultrametric, the output > tree will also be ultrametric. (Also see: > http://blog.phytools.org/2016/04/average-trees-and-maximum-clade.html.) > > 2) The function averageTree trees to find the tree with the minimum sum > of squared distances to all the trees in a set. The tree is not > necessarily a member of the set. Any of a number of different distance > criteria can be used; however, if the distance criterion selected does > not use branch lengths (e.g., Robinson-Foulds distance) then the output > tree will also not have branch lengths. (Also see: > > http://blog.phytools.org/2016/04/consensus-methods-and-computing-average.html > .) > > 3) Finally, the function consensus.edges computes consensus edge lengths > based on a set of input trees with edge lengths and a consensus > topology. By default, this function computes the average edge lengths > across all trees in which each edge of the consensus topology is > present. The user can decide what to do if an edge is absent in a given > input tree. The tree can be ignored, and thus contribute nothing to the > consensus edge length for that particular edge, or the edge length for > that tree can be set to zero. This function has a third mode, which is > to merely compute the consensus non-negative least squares edge lengths > on the user-supplied consensus tree. If all the input trees are > ultrametric, then the computed tree will also be ultrametric. Note that > this is difference from just using ls.consensus because in > consensus.edges the LS edge lengths are computed on a fixed tree, > whereas in ls.consensus we optimize both the topology and edge lengths > given a set of trees. (Also see: > http://blog.phytools.org/2016/03/method-to-compute-consensus-edge.html.) > > maxCladeCred was also mentioned by another list member. This is a > function of phangorn that finds the tree (or trees?) in the input set > with the highest total clade probability. This is done by going clade by > clade in each tree of a set, and computing the relative frequencies with > which each clade is represented across the set (these are the posterior > probabilities for each clade), multiplying the clade relative > frequencies for each tree, and then selecting the tree with the highest > product. Since this procedure merely permits us to select a tree or > trees from our posterior distribution, our tree should generally be > fully resolved and ultrametric if the trees in our input set are fully > resolved and ultrametric. Note also that in a Bayesian posterior sample > our maximum clade credibility (MCC) tree will usually be represented > many times. If we find all instances of the MCC tree in our set, and all > instances are ultrametric, then computing the average edge lengths > across this set (e.g., using consensus.edges) will also produce a tree > that is ultrametric. > > All the best, Liam > > Liam J. Revell > Associate Professor, University of Massachusetts Boston > Profesor Asistente, Universidad Católica de la Ssma Concepción > web: http://faculty.umb.edu/liam.revell/, http://www.phytools.org > > On 1/24/2019 6:14 PM, Alina van dijk wrote: > > Hi everyone, > > > > Thanks Emmanuel and Joseph for sharing your thoughts! > > Emmanuel, today I tried multi2di and it works. But, if I understand > > correctly, this function transforms the dichotomies with branches of > length > > zero. So for me, in fact, doesn't solve the politomy. Right? > > Joseph, I'm only a begginer with R and this program already gives me a > lot > > of headache. > > It drives me crazy think in another program... hahahha > > Just kidding! :) > > But, nice to know that I have a plan B! > > I will take a look! > > > > Thanks in advance, > > Best Regards, > > > > Alina > > > > > > Em qua, 23 de jan de 2019 às 16:29, Emmanuel Paradis < > > emmanuel.para...@ird.fr> escreveu: > > > >> Hi Alina, > >> > >> Did you try multi2di() to remove polytomies? > >> > >> Best, > >> > >> Emmanuel > >> > >> Le 23/01/2019 à 17:41, Alina van dijk a écrit : > >>> Hi everyone, > >>> > >>> My name is Alina, I'm attending master degree in ecology and I have a > >>> little problem with my consensus phylogeny. I used 1000 phylogeny of > >>> birdtree to construct the consensus tree but now I need to insert the > >> dates > >>> in this consensus tree. > >>> > >>> To accomplish this idea, I tried different methods: > >> consensustree<-averageTree > >>> (tree,method="symmetric.difference") but the result is a consensus tree > >> in > >>> topology, binary and rooted but not ultrametric. For this problem I > used > >>> consensus_tree_ultrametric > >>> <-compute.brlen(consensustree,method="Grafen",power=1), but the edge > >>> lengths was altered. > >>> > >>> So, I used another method to make a consensus tree using phytools > >>> consensustree_another_method <- consensus.edges(multiphylo,method = > >>> "mean.edge") as a result, a ultrametric tree, rooted with consensus > edges > >>> lengths, but have polytomies :( > >>> > >>> I also tried using phylobase , proposed by Brian O'Meara in this link: > >>> > >> > https://grokbase.com/t/r/r-sig-phylo/12bn9x5gv4/why-no-branch-lengths-on-consensus-trees > >>> , > >>> but as a result, my consensus tree wasn´t ultrametric and the > >>> transformation also altered the edge lengths. > >>> > >>> I only need to insert the dates based on the trees dated by Jetz in > this > >>> consensus tree and as result, an ultrametric tree, with consensus edges > >>> lengths and no polytomy. > >>> > >>> Does anyone know how to solve that problem? > >>> > >>> Thanks in advance, > >>> Best Regards, > >>> > >>> Alina > >>> > >>> [[alternative HTML version deleted]] > >>> > >>> _______________________________________________ > >>> R-sig-phylo mailing list - R-sig-phylo@r-project.org > >>> https://stat.ethz.ch/mailman/listinfo/r-sig-phylo > >>> Searchable archive at > >> http://www.mail-archive.com/r-sig-phylo@r-project.org/ > >>> > >>> > >>> Pour nous remonter une erreur de filtrage, veuillez vous rendre ici : > >> http://f.security-mail.net/VKQxzoa2 > >>> > >>> > >> > > > > [[alternative HTML version deleted]] > > > > _______________________________________________ > > R-sig-phylo mailing list - R-sig-phylo@r-project.org > > https://stat.ethz.ch/mailman/listinfo/r-sig-phylo > > Searchable archive at > http://www.mail-archive.com/r-sig-phylo@r-project.org/ > > > [[alternative HTML version deleted]] _______________________________________________ R-sig-phylo mailing list - R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo Searchable archive at http://www.mail-archive.com/r-sig-phylo@r-project.org/
