Hi Jarrett,
First, there are a lot of tools in the bioinformatics community that can
convert FATSQ files to FASTA far more efficiently than ape does (I think
cutadapt can do that, but surely many others too). But with a small file like
this one, ape can do the job :)
See below for specific ans
at would work? I'm not sure how to make ape::node.dating()
>> accept a
>> >> substitution rate rather than try to estimate one. Maybe an option
>> could be
>> >> added to allow mu to equal a user-specified number rather than the
>> output
>> >> of ape:
e I could also apply that logic to date all
> of the nodes by using the mean pairwise distances between taxa on either side
> of a node and converting that to divergence times (although the R code for
> such
> a calculation would likely take me a while to figure out). Would that be
>
Hi Vincenzo,
There's no direct way to do this with ape::chronos(). You may have a look at
the function phangorn::pml_bb() but I'm not sure it can estimate the dates if
the rate is provided in a model object given as main argument(?)
That said, I expect that estimating so many dates to be very c
Hi Russell,
There are several implementations of LTT plots among several packages, so the
details certainly differ depending on which one(s) you use.
Maybe you can use the ape function ltt.plot.coords() which returns a matrix
with 2 columns giving the number of lineages for each node time of
Hi Lior,
R-squared and Pearson's coefficient are two different things:
R-squared (aka coefficient of determination) quantifies the quantity of
variance of a variable (the response, 'y' in your example) that is explained by
the model where some predictors can be controlled by the experimenter. T
To follow (tangently) on Klaus' message, I've released a book last year on some
advanced topics in R programming and development:
https://hal.ird.fr/ird-03850685
Chapter 9 is on parallelization and HPC. There are a few (detailed) examples
showing when multi-core is benefitial and when it is not
Hi Vojtěch,
The GH repos for ape is:
https://github.com/emmanuelparadis/ape
I had a quick look at your code and these are interesting improvements. It
seems also possible to improve the basic code of dist.topo() (e.g., using
bitsplits) so it is worth opening an issue.
Cheers,
Emmanuel
-
Hi Kevin,
Do you run the checks of a new version of windex on this site:
win-builder.r-project.org/
? It runs the checks both on Debian and Windowns with several choices of R
versions, and you can access the detailed log files.
Best,
Emmanuel
- Le 28 Fév 23, à 17:38, Arbuckle kevin.arbuc
sppDist' that returns
> intraspecific and interspecific distances. However, it differs as well, so
> there is some added confusion.
> x3 <- sppDist(anoDist, anoSpp)
> intra <- x3$intra
> inter <- x4$inter
This gives me:
R> identical(x3$intra, intra1)
[1] TRUE
Be car
Hi Jarrett,
If you have a vector of species names (say 'taxa'), then:
o <- outer(taxa, taxa, "==")
returns a logical matrix with TRUE when the two strings in 'taxa' are the same,
FALSE if they are different (so the diagonal is TRUE). Since you return the
output of dist.dna() as a matrix, then
Dear all,
Registration is now open:
https://meeting-nstda.webex.com/meeting-nstda/j.php?RGID=r49da897c6a68260a5bf2bdf41763bcba
Cheers,
Emmanuel
___
R-sig-phylo mailing list - R-sig-phylo@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-phyl
(Posted to: r-sig-phylo and GitHub)
Hi all,
is.monophyletic() does not work correctly when some tip labels are
duplicated. Here's a simple example:
R> tr <- read.tree(text = "((A,B),(A,C));")
The two tips labelled "A" are not sister-lineages, but the current
version of ape gives:
R> is.mo
Hi Martin,
Rates are generally relative quantities in phylogenetics. You cannot estimate
the substitution rate(s) together with the branch lengths of the tree, but
rates can be estimated relative to each others. That's why one rate is fixed to
1 in the GTR model.
In the JC69 model the (single)
Ha! That's because gaps are coded with dashes in your files; I assumed it was
X's (as returned by ape::trans). So this line 7 should be:
foo <- function(x) sum(x == 0x58 | x == 0x2d)
Or (probably easier to modify):
foo <- function(x) sum(x == charToRaw("X") | x == charToRaw("-"))
Cheer
Hi Vojtěch,
In addition to removing lines 3 and 4, replace line 7:
foo <- function(x) sum(x == 4)
by:
foo <- function(x) sum(x == 0x58)
That sh(c)ould do it.
Best,
Emmanuel
- Le 2 Nov 21, à 17:37, Vojtěch Zeisek vo...@trapa.cz a écrit :
> Hello,
> I try to trim protein alignmen
Hi Jake & Diego,
Maybe a very small modification to ace() could help to accomodate some of these
issues. Currently, ace(type = "discrete") checks the branch lengths of the tree
and throws an error if any of them is zero or negative. I think zero-length
branches could be allowed. This seems quit
Hi,
A tree has n terminal nodes (aka tips) and m internal nodes (aka nodes simply).
In the edge matrix, the tips are numbered 1:n and the nodes are numbered
(n+1):(n+m) (same than n+1:m). n and m can be found with:
n <- Ntip(tree) # or length(tree$tip.label)
m <- Nnode(tree) # or tree$Nnode
De
Hi Jarrett,
- Le 28 Juin 21, à 5:08, Jarrett Phillips phillipsjarre...@gmail.com a
écrit :
> Hello All,
>
> I have a COI FASTA alignment file with 11926 sequences spanning 668 species.
>
> According to my code, a total of 361 species are represented by 6 or more
> sequences.
>
> I need to
Hi Yan,
- Le 18 Mai 21, à 23:48, Yan Wong y...@pixie.org.uk a écrit :
> Dear R-Sig-Phylo,
>
> I’m interested in representations of ancestral recombination graphs (ARGs).
> From
> my reading of the extended Newick format (G. Cardona et al., 2008), and the
> ape/evonet documentation, it appear
Hi Russell ,
It can happen that PGLS models have difficulties to fit to the data when there
is a free parameter in the correlation structure. This is the case of
corMartins and corPagel. A way around is to set 'fixed = TRUE' when creating
these correlation structures which has the effect of ta
hat all variables are ordered correctly whether
they are involved as predictors (in 'model = '), in the correlation structure,
or in the variance function ('weights = ').
Best,
Emmanuem
> Anyway, thank you!
> Marguerite
> On Sun, May 16, 2021 at 7:03 PM Emmanue
Hi Marguerite,
The issue is about nlme::gls. The help page ?gls says:
data: an optional data frame containing the variables named in
‘model’, ‘correlation’, ‘weights’, and ‘subset’. By default
the variables are taken from the environment from which ‘gls’
is calle
Hi Jarrett,
- Le 27 Avr 21, à 0:09, Jarrett Phillips phillipsjarre...@gmail.com a écrit
:
> Hi All,
>
> I'm looking for a way to extract singleton haplotypes using the haplotype
> function in Pegas.
>
> I use the below function to accomplish this:
>
>extract.singleton.haps <- function(
Hi Juan,
There is a bug in pcoa() when only one axis is selected by the function. You
can fix it by editing the function with fix(pcoa) and modify line 38 (or close
depending on how the editor arranges the lines of code):
vectors <- sweep(D.eig$vectors[, 1:k], 2, sqrt(eig[1:k]), FUN = "*")
ins
Hi Jacob,
ape::makeNodeLabel(phy, method = "md5sum") returns 'phy' with node labels that
depend on the tips descendant from each node. For instance:
tr3 <- makeNodeLabel(rtree(3), m = "m")
tr4 <- makeNodeLabel(rtree(4), m = "m")
any(tr3$node.label %in% tr4$node.label)
If you repeat these 3 comm
Hi Joe,
I'd say this issue is related to these particular data: there are four states
so the ARD model has 12 parameters which is quite a lot considering that one
state ('3') is overwhelming represented in the data. If you simulate data with
two states, then the ARD model has only 2 parameters
Hi Matt,
You can think about a randomization procedure: rTraitDisc(), rTraitCont(), and
rTraitMult() all have the option 'ancestor' to output the values of a trait
simulated along a phylogeny for all terminal and internal nodes.
HTH
Best,
Emmanuel
- Le 27 Jan 21, à 0:42, Matthew Helmus m
Hi Saleh,
Two functions in ape can help you:
?zoom
?trex
There may be others in other packages.
Best,
Emmanuel
- Le 19 Jan 21, à 19:42, Saleh Rahimlou saleh_rahim...@hotmail.com a écrit :
> Hello,
>
> How can I collapse some clades plotting a big phylogenetic tree to magnify my
> favori
Hi Chris,
It is not clear from your message where the error occurred. Can you please send
a reproducible example? I don't think the last model fit (output named 'OLS')
gives an error since gls() with no correlation structure is equivalent to using
lm().
Also if you use fixed=1 this is the same
Hi Joseph,
Thanks for reporting this. It seems indeed that reordering the output of
bind.tree() fixes it. A way to do it is:
attr(t2, "order") <- NULL
t2 <- reorder(t2)
It seems to solve the different problems (balance(t2) doesn't work correctly
too). I'll add these 2 lines as the end bind.tre
Hi Yan,
You're correct: multi2di() calls rtree(, equiprob = TRUE) which generates the
random topology. Actually, the unlabelled topologies are generated with equal
probabilities. For the labelled topologies, this is a bit more complicated. In
the case n = 4 tips, there are two unlabelled topolo
Hi,
Actually, Ranjita can use the number of gene copies if it is reasonable to
assume that these numbers evolve among samples, maybe a stepwise model with
transitions:
n -> n + 1
n -> n - 1
In that case, a simple approach is to calculate the Euclidean distances among
samples and do an NJ or
Hi Elvira,
If you are interested in keeping the "surviving species" from phylogenies, it
may be better to use a birth-death model to simulate the trees. There are 3
functions in ape to do this: they are documented in the same help page than
drop.fossil() and they have options that make them qui
Hi all,
The current version of ape on CRAN (5.4) has a bug in its function
boot.phylo: all returned values are 0. The bug has been fixed; however,
because it was in ape's internal C code, this requires a complete
reinstallation of the package. A new version of ape with the version
number 5.4-
Hi Kelly,
Thanks! This is fixed.
Best,
Emmanuel
- Le 1 Juil 20, à 23:20, Kelly Street street.ke...@gmail.com a écrit :
> Hello,
>
> Thank you for all your work developing and maintaining this great package!
> This is likely a known issue already (and not a critical one), but since
> the u
Maybe there is also a connection between tree ranking and topological distances
(see ?nni in phangorn).
Best,
Emmanuel
> Cheers
>
> Yan
>
>> On 27 Jun 2020, at 10:33, Emmanuel Paradis wrote:
>>
>> Hi Yan,
>>
>> multi2di() calls rtree() if random = TRUE.
Hi Yan,
multi2di() calls rtree() if random = TRUE. As you rightly guessed, the
algorithm used by this latter function is (described in APER2, p. 313):
1. Draw randomly an integer a on the interval [1, n − 1]. Set b = n − a.
2. If a > 1, apply (recursively) step 1 after substituting n by a.
3. Re
Hi,
Brian is 100% right about interpreting bootstrap values. When the tree is input
into R with read.tree() or read.nexus(), these values are attached to the nodes
but they relate to their subtending branches. The function root() has the
option 'edgelabel' to specify whether these node labels m
Hi Jarrett,
I'm Cc'ing to r-sig-genetics since we had a recent discussion on a similar
topic (see below).
- Le 14 Mai 20, à 9:59, Jarrett Phillips phillipsjarre...@gmail.com a écrit
:
> Hello,
>
> Emmanuel Paradis has recently updated the haplotype() function in pega
is one thing I did not think of yet, and you can help me figure
> it
> out. In any case, thank you for your help. I really appreciated it.
> Kind regards,
> Coline
> From: Emmanuel Paradis [mailto:emmanuel.para...@ird.fr]
> Sent: Monday, 6 April 2020 16:47
> To: Coline Boo
ity matrix (converted to a matrix:
is.complex(as.matrix(mat_dissim_Eucl)) ) R gives me the result FALSE. That
means that there are no complex numbers in the input for the pcoa, right?
I hope you or someone else has another suggestion on why I get this error.
Kind regards,
Coline
From
Hi Coline,
This is strange: you calculate a distance matrix with daisy(), so the
as.matrix() operation should return a symmetric matrix. Symmetric (real)
matrices have all their eigenvalues real numbers. Maybe some complex values
were produced by daisy()?
Best,
Emmanuel
- Le 30 Mar 2
Hi Karla,
ape has several functions to simulate trees that make use of these formulas
(see ?rphylo). However, the formulas you are looking for may not be directly
accessible from R, so you need to check the sources of ape. You may also need
to use the last testing version of ape since a bug was
Hi Jarrett,
read.FASTA() always returns a list. So you may do something (quite general)
like:
fls <- dir(pattern = "\\.fas$|\\.fasta$", ignore.case = TRUE) # add more file
extensions if needed
X <- lapply(fls, read.FASTA)
seqlen <- lengths(X)
if (length(unique(seqlen)) == 1) X <- as.matrix(X)
Hi Hirra,
I've tried with the data you pisted below using pegas 0.12 and I was not able
to repeat your results: I found that seqs. 1 and 3 are grouped in the same
haplotype (not 1 and 2). Anyway, this is the same issue that you pointed out a
few days ago: seq. 3 could be grouped with seq. 1 or
d be options to control this algorithm:
- exit after step 1.
- ignore step 2.
At step 5, it seems to make sense to start with the "shortest" sequences and
pool them with the "longer" ones, ie, "A-" would be pooled with "AA".
Comments and suggestion
Hi Hirra,
The assignment is not random, it follows the order of the sequences in the data:
- Seqs. A and B are compared and found to be identical so they are both
assigned to haplotype I.
- Seq. C is compared to haplotype I (effectively seq. A) and found to be
different so it is assigned to hap
Hi,
To answer Elizabeth's question: there is no function that does what
you asked for in your first message. Liam's solution is certainly the
best solution for the moment. I'll have a look at it later. The code
checkValidPhylo() needs to be dusted off a bit: the diagnostic "
MODERATE: some no
Hi Liam,
I paste below a fixed version of drop.tip(). It seems to work
correctly but please test is as much as you want.
Best,
Emmanuel
===
drop.tip <-
function(phy, tip, trim.internal = TRUE, subtree = FALSE,
root.edge = 0, rooted
Hi Mario,
In the class "phylo", nodes and tips are numbered sequentially so it
is no problem to have data associated with both. This is done in many
functions in ape and in phangorn. I think the solution to your
headaches is in this document (§ 4.4):
http://ape-package.ird.fr/misc/FormatTree
Hi Saleh & Will,
I'm not sure whether phytools::cophylo does the same thing than
ape::comparePhylo (maybe rather ape::cophyloplot).
comparePhylo() is actually aimed for data exploration/summary rather
than for producing publication-ready graphs. That said, there is a
trick to play with the chara
Hi all,
The package 'phylobench' has recently been released on GitHub. It aims
to provide tools for "phylogenetic benchmarking" by performing data
analyses, tests, or simulations using functions in other packages, and
comparing the outputs with expected or predicted values. Currently, 12
benc
:)
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
mailto:emmanuel.para...@ird.fr>> escreveu:
Hi Alina,
Did you try multi2di() to remove polytomies?
Best,
Emmanuel
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
Hi Jérémie,
You're correct: the current version of write.tree() scales with n^2.
This seems to be related to calling the generic '[[' operator. You can
modify the code with the usual fix(write.tree), then insert these two lines:
phy <- .uncompressTipLabel(phy)
class(phy) <- NULL
righ
Hi David,
Have you tried ape::plotBreakLongEdges? I think that would be the
simplest solution to your problem. I'm not clear how a non-linear
transformation could be implemented easily (and be meaningful in most
situations).
Le 02/01/2019 à 21:15, David Bapst a écrit :
Hi all,
I've been de
Hi John,
It looks like that the constraints on the dates with the 4 calibrations
are such that the penalized likelihood cannot be calculated. There are
several occasions when a value of -1e100 is returned (non finite value,
negative branch lenghts, ...) so it's hard to see what is the problem
Hi David,
phangorn has the function consensusNet that builds consensus networks
(objects of class "networx") which is more appropriate than
ape::consensus is p < 0.5. There is a nice plotting function using RGL
for "networx" objects. Of course, you won't get a fully bifurcating tree
if there
n no
correction is defined by the user.
-Dave
On Tue, Oct 23, 2018 at 10:26 PM Emmanuel Paradis
mailto:emmanuel.para...@ird.fr>> wrote:
Hi David,
Have you tried one of the two possible corrections?
R> res <- pcoa(dmat)
R> res.lingoes <- pcoa(dmat, correct
Hi David,
Have you tried one of the two possible corrections?
R> res <- pcoa(dmat)
R> res.lingoes <- pcoa(dmat, correction = "lingoes")
R> res.lingoes$note
[1] "Lingoes correction applied to negative eigenvalues: D' = -0.5*D^2 -
0.310850908498892 , except diagonal elements"
The matrix $values
Hi Zhong,
A few good places where to start:
http://ape-package.ird.fr/
https://github.com/KlausVigo/phangorn
For basic introductions, see the vignettes in the package phangorn:
https://CRAN.R-project.org/package=phangorn
Best,
Emmanuel
Le 25/09/2018 à 17:34, Zhong Huang a écrit :
Hello,
ulated for a 3x3 matrix, so this can be generalized to
different dimensions (even non-square). The options of rect() can be
used (border, ...)
par(xpd = TRUE) is to make the heatmap at the root completely visible.
Best,
Emmanuel
Le 30/08/2018 à 12:45, Emmanuel Paradis a écrit :
Hi Jacob,
Hi Jacob,
It is possible to call nodelabels() several times to do something
similar to what you want by playing with the adj argument which is
c(0.5, 0.5) by default (ie, the label is centered on the node). You can
try this:
tr <- rcoal(5)
plot(tr, "p", FALSE)
for (h in c(0.4, 0.5, 0.6))
f
Hi Agus & Brian,
To complete Brian's response, vcv() is a generic function which works
with trees (class "phylo") and phylogenetic correlation structures
(class "corPhyl"). The latter can be used to define an OU model, see
?vcv, and ?corPhyl for the correlation structures available in ape.
B
Hi Nick,
This can be fixed by editing the code of tiplabels() with the usual
procedure:
fix(tiplabels)
then find this line of code:
tmp <- rect2polar(XX, YY)
and insert below the following one:
if (lastPP$align.tip.label) tmp$r[] <- max(tmp$r)
save and close. Your commands wor
then set column x to one in the matrix of
likelihoods:
1 0 0 0 # if the base observed is A
0 0 1 0 # if the base observed is G
1 0 1 0 # if the base observed is R
...
1 1 1 1 # if the base observed is N
This can be applied to any character with more than two states.
Best,
Emmanuel
Le 22/06/20
Hi Théo,
It is possible to modify the code of ace() to take uncertain character
states into account. If you edit the code with fix(ace), after these
four lines:
if (method != "ML")
stop("only ML estimation is possible for discrete characters.")
if (any(phy$edge.length <= 0))
Hi Sebastian,
All the likelihood-based phylogenetic inference functions have been
removed from ape since version 2.4 (released in Oct 2009) because of the
(incomparably better) implementation in phangorn:
library(phangorn)
?SH.test
Best,
Emmanuel
Le 08/06/2018 à 14:50, Sebastian Y. Müller
Hi John,
See my comments below.
Le 09/04/2018 à 16:46, jschenk a écrit :
Hi Folks,
I have been banging my head against what appears to be an easy coding problem
for a while now and haven’t been able to hack my way out of it. I am running a
function to identify a posterior set of node ages f
Dear Watal,
Thank you. This is now in ape.
I've just uploaded a new testing version (5.0-5) with the last changes
and fixes on ape's site:
http://ape-package.ird.fr/ape_installation.html#versions
A Windows version is available. The list of changes are listed there:
http://ape-package.ird.fr
Hi Santiago,
This approach is implemented in phangorn, from ?optim.pml:
If the option 'optRooted' is set to TRUE than the edge lengths of
rooted tree are optimized. The tree has to be rooted and by now
ultrametric! Optimising rooted trees is generally much slower.
Cheers,
Emmanu
Hi,
To get a tree with a basal multichotomy as a rooted tree, you have to
set its root edge:
R> tr <- read.tree(text = "(A,B,(C,D));")
R> is.rooted(tr)
[1] FALSE
R> tr$root.edge <- 0
R> is.rooted(tr)
[1] TRUE
This could be done directly in the Newick string:
R> tr <- read.tree(text = "(A,B,(
t: because of the namespace it is better to
source plot.phylo() at the same time.
Best,
Emmanuel
Le 23/12/2017 à 22:48, Emmanuel Paradis a écrit :
Hi Walter,
That shouldn't be too hard to fix. This happens, apparenly, only if
type="phylogram" -- which is the default. This se
Hi Walter,
That shouldn't be too hard to fix. This happens, apparenly, only if
type="phylogram" -- which is the default. This seems to work correctly
if type="c" (and if there are branch lengths).
I'll update you when it's fixed.
Best,
Emmanuel
Le 20/12/2017 à 22:17, Walter, Mathias a écri
Hi,
You can find all released versions of ape as source packages on CRAN:
https://cran.r-project.org/src/contrib/Archive/ape/
Best,
Emmanuel
Le 07/12/2017 à 11:19, pascal de Clarens a écrit :
Hello,
I am using Iramutec working togethr with R
it needs to use ape 3.5 annd having installed and
Hi Andreas,
This sounds more like an issue with RStudio which seems to freeze from
time to time, unless you have a reproducible example under another
environment.
Best,
Emmanuel
Le 30/10/2017 à 15:38, Andreas Kolter a écrit :
If I paste() a huge DNAbin alignment (by accident) (as in: 250MB
Hi Vojtěch,
Here's something you could do. First, make a copy of del.colgapsonly:
toto <- del.colgapsonly
Then, edit this copy (e.g., with fix(toto)), find this line:
foo <- function(x) sum(x == 4)
and replace 4 by 240. Save and close. Now you can use toto() in the same
way than del.colg
Hi Dave,
The seed is created every time you generate random data (see details in
?.Random.seed):
R> exists(".Random.seed")
[1] FALSE
R> sample(1)
[1] 1
R> exists(".Random.seed")
[1] TRUE
So in your code below the seed is created by calling rtree(). Indeed,
with ape 4.1:
R> rm(".Random.seed
ut I will check again later
today to see if it changes.
All of the best,
Elizabeth
On Oct 17, 2017, at 2:47 PM, Emmanuel Paradis wrote:
Hi Elizabeth,
I have submitted ape 5.0 on CRAN on 5 October but I'm still waiting for
feedback. I suspect there are problems with reverse dependencies. In t
Hi Elizabeth,
I have submitted ape 5.0 on CRAN on 5 October but I'm still waiting for
feedback. I suspect there are problems with reverse dependencies. In the
meantime, I cleared the testing repositories thinking that CRAN would
take the usual 1-2 days to publish the new version. Sorry for the
H
Best,
Rafael Maia
—
Junior Fellow, Simons Society of Fellows
Rubenstein Lab, Columbia University
Department of Ecology, Evolution and Environmental Biology
New York, NY
http://www.rafaelmaia.net
On Sep 26, 2017, at 9:03 AM, Emmanuel Paradis <mailto:emmanuel.para...@ird.fr>> wrote:
Hi Elizabeth,
You can use directly the functions behind the calculations of the
coordinates; they are documented together: ?node.depth. But this will
not give the final coordinates since more calculations are needed
depending on the widths of the labels, etc.
Another possibility could be to
Hi Wouter,
confint() uses the normal approximation of the likelihood function, not
profiling. In the example you give, confint.default() is used because
'm' does not inherit the class "glm". As you wrote below, this usually
gives CIs too small (as explained in ?binaryPGLMM) and symmetric where
Hi George,
Nice comparison! It would be interesting to see if the difference
between ape and rncl is always in the same direction. It seems that the
trees in your test are all relatively small (timings are concentrated
around 1 ms). Apparently, read.tree scales a bit better than
read_newick_p
There is also an implementation of this method in two functions in ape, see:
?pic.ortho
?varCompPhylip
There are examples with simulated data in both help pages. The second
function requires PHYLIP (similarly to Rphylip) .
Best,
Emmanuel
Le 04/08/2017 à 14:36, Joe Felsenstein a écrit :
The
Hi,
This was asked some time ago:
http://www.mail-archive.com/r-sig-phylo@r-project.org/msg04388.html
HTH
Best,
Emmanuel
Le 30/07/2017 à 10:58, LUCAS A. (599841) a écrit :
Hi
(This is my first query to a group like this, so my apologies if the subject is
a little basic)
I have a data set
Dear all,
A new version of ape is in preparation with several significant changes.
The most important ones are:
- All types of phylogenetic trees and networks are now supported:
* trees with singleton nodes are handled with the usual functions
read.tree, plot.tree, ...
* networks are read/writ
Hi Lydia,
This kind of problem happens sometimes though it's not clear why. One
possibility is that the Pagel model is not appropriate for your data.
One thing you can do is to estimate lambda by repeatedly fitting models
with fixed = TRUE for different values of lambda between 0 and 1, and
s
Hi Santiago,
For the tree 'rtr' below, the default size of the graphical device is
indeed too small: you can maximize the window size and this should work
(or you can set manually x.lim). After plotting the tree this way, you
can reduce the size of the window and have no problem. It's fixed no
.
HTH.
JWB
Joseph W. Brown
Post-doctoral Researcher, Smith Laboratory
University of Michigan
Department of Ecology & Evolutionary Biology
Room 2071, Kraus Natural Sciences Building
Ann Arbor MI 48109-1079
josep...@umich.edu <mailto:josep...@umich.edu>
Joseph, Klaus,
This is great. I slightly edited the code and renamed the argument
'tips' to 'tip' (as in the original definition). I run on a bunch of
random trees and the results are exactly identical with the current
version of getMRCA. I'm changing the code in ape now.
Cheers,
Emmanuel
Elizabeth,
Thanks a lot for the detailed account of this problem. I've just made
these modifications to the code of phydataplot:
1/ Replaced:
lgd <- as.character(ux)
with:
lgd <- sort(as.character(ux))
2/ These two lines:
conames <- names(co)
if (!is.null(conames)) co <- c
Hi Elizabeth,
Thanks for the report. Apparently, it's enough to add:
if (is.null(p)) p <- 1L
after:
p <- ncol(x)
Best wishes,
Emmanuel
Le 23/05/2017 à 20:31, Elizabeth Purdom a écrit :
Hello,
I am writing to the R-sig-phylo mailing list regarding what seems to be
a bug in the `ph
Hi Juan,
This warning seems related to the fact that the trait did not evolve
according to the specified model (i.e., Brownian motion). I simulated
some data with:
tr <- rphylo(50, .1, 0)
x <- rTraitCont(tr)
ace(x, tr)$sigma did not return NA out of 1000 replications. I changed
the
Hi Salvador,
You first need to define the variables that would be resampled during
the bootstrap procedure. In the case of DNA sequences, this would be the
columns (= sites) of the alignment, since they each contribute to the
distance calculation (or to the likelihod function if you use ML). S
Hi,
If you have a single tree (object of class "phylo")
phy$root.edge <- 0
If there are several trees in your NEXUS file (then phy is of class
"multiPhylo"):
for (i in seq_along(phy)) phy[[i]]$root.edge <- 0
Best,
Emmanuel
Le 07/02/2017 à 13:17, Yan Wong a écrit :
Sorry if this is a triv
Dear Andreas,
There is no distance formula for HKY or GTR model. For GTR, Rodrı́guez
et al. developed a procedure to calculate a distance (also in Yang's
2006 book). An example is given below with the woodmouse:
matlog <- function(x) {
tmp <- eigen(X)
V <- tmp$vectors
U <- diag(lo
Hi Sérgio,
It seems your results make good sense. alpha=0 is too far from the
"optimum" value (i.e., the value that maximises the log-lik), so the
optimisation fails to maximise the log-likelihood with respect to this
parameter. It has been written in the literature that it is difficult to
es
Hi Klaus,
Thanks for tracking this. It's fixed.
Best,
Emmanuel
Le 20/01/2017 à 18:41, Klaus Schliep a écrit :
Hi Juan,
it seems that you trim too many taxa.
I can replicate the error message if I trim for example 19 out of a 20 tips
of a tree.
drop.tip(tree, sample(20, 19))
Error in integer(
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