Re: [R-sig-phylo] 3. partial correlation with gls residuals? (Tom Schoenemann)

[Emmanuel Paradis]

Hi Alejandro,

I agree with almost all your points. A few additional comments below.

"Correlation" gives the correlation among the estimated regression 
parameters: it is computed from the variance-covariance matrix extracted 
from the fitted object, model.fit$varBeta or vcov(model.fit) -- the 
latter is not to be confused with vcv(). It depends on the shape of the 
likelihood function and shows how much the estimation of a parameter may 
be affected by others.


On phylogenetic signal, I think that AIC may be a suitable way to select 
the appropriate correlation structure: fit the same regression model 
with different corStruct and select the one with the smallest AIC. Note 
that often, the corStruct for a given regression model will not be the 
same than when considering each variable separately (e.g., gls(A ~ 1, ...)


A more general comment to Tom: you seem to imply the following (causal) 
relationships (here '->' is not R's operator):


C -> A
C -> B

It seems pretty clear to me that, if these relations hold, A and B will 
be correlated. But maybe you have other hypotheses/models in mind.


Best,

Emmanuel

Alejandro Gonzalez wrote on 13/03/2012 16:04:

Hello Tom,

I will answer some of your questions below, Emmanuel and others may be better 
placed to reply to some of your questions:


On 12, Mar 2012, at 7:49 PM, Tom Schoenemann wrote:


Thanks Rob and Alejandro,

OK, I did as suggested and ran a PGLS with A ~ B + C.  I was hoping for some 
clarification of the actual results.  Here is a summary:

**
Generalized least squares fit by maximum likelihood
  Model: variableA ~ variableB + variableC
  Data: DF.B.A.C
AIC   BIC  logLik
  -23.49499 -10.46914 16.7475

Correlation Structure: corPagel
Formula: ~1
Parameter estimate(s):
 lambda
-0.09862731

Coefficients:
  Value  Std.Error   t-value p-value
(Intercept)   0.5229794 0.04740728 11.031625  0.
variableB 0.2200980 0.05012508  4.390976  0.
variableC   0.0620030 0.05128472  1.208996  0.2296

Correlation:
  (Intr) variableB
variableB -0.813
variableC0.362 -0.837

Standardized residuals:
   Min Q1Med Q3Max
-3.2951355 -0.4995948  0.2604608  0.8884995  2.8456205

Residual standard error: 0.2067425
Degrees of freedom: 100 total; 97 residual
**

Are the following correct interpretations?:

1) Controlling for the phylogeny I used, variableB is associated with variableA 
independent of variableC, because the p-value of the beta weight for variableB 
is highly significant (0.)


Yes, the model estimates a partial regression slope and standard error, that is 
the relationship between B and A controlling for the potential effects of C 
(that is potential relationship between C and A).



2) Controlling for the phylogeny I used, variableC is not significantly 
associated with variableA independent of variableB, because the p-value of its 
beta weight is not significant (0.2296)


Yes, assuming there is no multicolinearity. See below...



3) There does not seem to be a significant effect of phylogeny on this 
relationship, since the ML lambda estimate is: -0.09862731


Yes, when lambda tends to 0, phylogenetic and non phylogenetic methods are 
expected to converge. I will note that an advantage of using PGLS methods is 
that the evolutionary parameter estimated simultaneously with model fit (in 
this case lambda) allows for adequate adjustment for phylogenetic signal. See a 
nice paper on this by Revell 2010 in Methods in Ecology and Evolution.




Also, what exactly are the values listed in the "Correlation" section? Does the 
-0.837 entry indicate that variableB is correlated negatively with variableC controlling 
for variableA (and/or my phylogeny)?


Maybe Emmanuel can answer this one. You could test whether B and C are strongly 
correlated, for example using PGLS. If they are repeating the analysis dropping 
B from your model should result in a significant correlation between C and A, 
indicating there is multicolinearity. Of course, the proper way to do all this 
is to examine your data prior to analyses. What are the two traits, maybe they 
are providing very similar information?




Regarding my original plan to assess the independent relationship between 
variables using residuals, the Freckleton paper Alejandro kindly forwarded 
includes this comment:

"Note that to estimate the true slope for the effect of x2 using residual regression 
one would need to regress the residuals of the regression on y on x1 on the residuals of 
the regression of x2 on x1 (e.g. see Baltagi 1999, pp. 72ˆ74 for elaboration of 
this)." (p. 544)

This was what I remembered about the issue myself, though I haven't kept up on 
the literature Rob and Alejandro mentioned.

However, Rob believes the residuals might not be independent of phylogeny,

Re: [R-sig-phylo] parafit

[Jarrod Hadfield]

Hi Juan,

Thank you for your answer - this makes sense to me. However, could the
same not be said for the unormalised eigenvectors of A as they preserve
the original similarities among the taxa, have the same units etc.?
Also, since solve(A) has the same eigenvectors as A but with reciprocal
eigenvalues it has some of these properties too.

I'm not saying that PCO of J-A is bad, but what I would like to know is
whether PCA of solve(A) could be considered as an equal alternative.

Cheers,

Jarrod




On Wed, 2012-03-14 at 11:58 +0100, Juan Antonio Balbuena wrote:
> Hello,
> I think the reason for using principal coordinates in parafit is that
> taken all together the PCO axes preserve the original dissimilarities
> among the taxa and can thus the resulting ordination is an exact
> representation of the host and parasite phylogenies in the hyperspace.
> In addition, the scales of the PCO axes are interpretable in the units
> of the original resemblance measure. 
> 
> Cheers
> 
> Juan A. Balbuena
> 
> 
> 
> > Hello Everyone,
> > 
> > I am fitting mixed models in which I have two phylogenies and I would
> > like to understand them in the context of earlier work. In parafit
> > (Legndre 2002) principal coordinates of the distance matrices (J-P) are
> > used, where J is a matrix of ones and P the phylogenetic correlation
> > matrix.  For me, using unnormalised eigenvectors of solve(P) would
> > result in nicer properties, and I wonder whether anyone could tell me
> > whether there is some deep motivation for using the principal
> > coordinates of J-A that I'm missing?
> > 
> > Kind Regards,
> > 
> > Jarrod
> > 
> > ___
> > R-sig-phylo mailing list
> > R-sig-phylo@r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
> > 
> > 
> 
>

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[R-sig-phylo] Tree Permutation

[Sean Downey]

Hi,

I've banged my head long enough with this one, so I hope someone can help. I am 
trying to write a routine to permute the structure of a tree. Note, this is 
different than phyloshuffle() in phylotools, which just shuffles tips -- in 
contrast, I am trying to permute the structure of the tree. In this case I 
cannot resample the original data because these trees are manually constructed, 
yet I want a way or doing some statistics on them. If there is a package doing 
this that I've missed? I would like to be able to specify a number of 
iterations (easy) and the routine would repeatedly switch random pairs of 
clades within the tree (not so easy, apparently). If the routine is run for 
many iterations, the resulting tree would be completely random. This seems 
simple, but given the dependencies in the tree, you can't pick just any two 
nodes; for example, the second node cannot be a descendant of the first node. 
Also, it seems like I need to test that the two subtrees are structurally !
 independent, but I'm not certain exactly what these criteria are. They don't 
appear to have to be the same distance from the root in all cases. The next 
problem is how to do this in ape. I'm reasonably familiar with the phylo() 
object, but obviously since I'm posting this, I haven't been able to make it 
work. Especially, the bind.tree() step. 

Thanks much for any help,

Sean

## Tree Permutation
## Note, code does not work correctly!

library(ape)
library(distory)
atree<-read.tree(text="((L1496,L1499),((L1498,L1490),((L1497,L1494),((L1493,L1492),(L1503,(L1502,(L1212,L1501)),L1489);")
atree<-makeNodeLabel(atree, prefix = "")
atree<-compute.brlen(atree,1)

n=1 # No. itterations

plot.phylo(atree, show.node.label = TRUE)
ptree<-atree # a copy to permute
for (i in 1:n){
  # Pick the first node from the tree
  a.node<-as.numeric(sample(ptree$node,1))
  a.node <- 2 # testing

  # This creates a subtree to sample the second branch from
  extract.a<-extract.clade(ptree,node=as.character(a.node))
  drop.a.node<-drop.tip(ptree,extract.a$tip.label, trim.internal=F) #trim F to 
leave a place to attach other subtree
  plot(extract.a, show.node.label = TRUE)
  plot(drop.a.node, show.node.label = TRUE)
  
  # Pick a node from somewhere ealse in the tree
  b.node<-as.numeric(sample(drop.a.node$node,1))
  b.node <- 5 #testing
  
  # This creates a subtree to sample the second branch from
  extract.b<-extract.clade(drop.a.node,node=as.character(b.node))
  drop.b.node<-drop.tip(drop.a.node,extract.b$tip.label, trim.internal=F)
  plot(extract.b, show.node.label = TRUE)
  plot(drop.b.node, show.node.label = TRUE)
  
  #   drop.b.node contains whatever is left after clipping out the two subtrees
  #   now I want to reassemble the tree switching extract.a and extract.b
  bind.tree.1<-bind.tree(drop.b.node,extract.a,where=b.node) # doesnt work?
  plot(bind.tree.1, show.node.label = TRUE)
  bind.tree.2<-bind.tree(bind.tree.1,extract.b,where=a.node)
  plot(bind.tree.2, show.node.label = TRUE)
  #copy the results
  ptree <- bind.tree.2
  }

#plot the permuted tree
plot(ptree, show.node.label = TRUE)

#END


*
Sean S. Downey, Ph.D.
Institute of Archaeology
University College London
31-34 Gordon Square
London
WC1H 0PY
s.dow...@ucl.ac.uk 
http://www.homepages.ucl.ac.uk/~tcrnssd/
UK Cell: +44 (0)7542 41 0077
Belize Cell: +501 636-2939

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[R-sig-phylo] Alternative to rapply() for nested lists of phylo objects?

[David Bapst]

Hello all,
I am dealing with simulation results that produce nested lists of trees
(with unbalanced depths; i.e. the first list might have five lists of three
trees, the second element might have three lists of five trees, the third
element might just be a single tree). I want to do some analyses on each of
these trees, so one option would be flattening the list and recording their
original position in the list. Alternatively, I'd prefer to retain the
structure of the nested list. I recently discovered rapply() and thought
this was a perfect fix, only to discover that it appears to look at the
type() and not the class() of objects passed to it, so it ignores the phylo
objects as a whole and passes right on to their constituent elements.

For example:

library(ape)
tree<-rtree(10)
list1<-list(tree,tree,tree)
list2<-list(list1,tree,list1)
rapply(list2,Ntip)

Playing with arguments in rapply doesn't stop this behavior; indeed, it
seems nothing will stop rapply from ignoring the type 'list' of the phylo
objects themselves. Does anyone know of an alternative to rapply that
considers the class of the nested objects instead?

Thanks,
-Dave B.

-- 
David Bapst
Dept of Geophysical Sciences
University of Chicago
5734 S. Ellis
Chicago, IL 60637
http://home.uchicago.edu/~dwbapst/
http://cran.r-project.org/web/packages/paleotree/index.html

 

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Re: [R-sig-phylo] Tree Permutation

[Rob Lanfear]

Hi Sean,

Conceptually speaking it helps to think about tree permutations in terms of
snapping a tree at a random edge, and then re-attaching that edge somewhere
else on the tree. That saves the problems with picking two independent
nodes. There are standard routines for this kind of thing, particularly
nearest-neighbour interchange (NNI), subtree prune and regraft (SPR), and
tree bisection reconnection (TBR).

I know that NNI and SPR are implemented in Phangorn, but I couldn't find an
implementation of TBR. Others will know if there is one.

Cheers,

Rob

On 14 March 2012 23:55, Sean Downey  wrote:

> Hi,
>
> I've banged my head long enough with this one, so I hope someone can help.
> I am trying to write a routine to permute the structure of a tree. Note,
> this is different than phyloshuffle() in phylotools, which just shuffles
> tips -- in contrast, I am trying to permute the structure of the tree. In
> this case I cannot resample the original data because these trees are
> manually constructed, yet I want a way or doing some statistics on them. If
> there is a package doing this that I've missed? I would like to be able to
> specify a number of iterations (easy) and the routine would repeatedly
> switch random pairs of clades within the tree (not so easy, apparently). If
> the routine is run for many iterations, the resulting tree would be
> completely random. This seems simple, but given the dependencies in the
> tree, you can't pick just any two nodes; for example, the second node
> cannot be a descendant of the first node. Also, it seems like I need to
> test that the two subtrees are structurally !
>  independent, but I'm not certain exactly what these criteria are. They
> don't appear to have to be the same distance from the root in all cases.
> The next problem is how to do this in ape. I'm reasonably familiar with the
> phylo() object, but obviously since I'm posting this, I haven't been able
> to make it work. Especially, the bind.tree() step.
>
> Thanks much for any help,
>
> Sean
>
> ## Tree Permutation
> ## Note, code does not work correctly!
>
> library(ape)
> library(distory)
>
> atree<-read.tree(text="((L1496,L1499),((L1498,L1490),((L1497,L1494),((L1493,L1492),(L1503,(L1502,(L1212,L1501)),L1489);")
> atree<-makeNodeLabel(atree, prefix = "")
> atree<-compute.brlen(atree,1)
>
> n=1 # No. itterations
>
> plot.phylo(atree, show.node.label = TRUE)
> ptree<-atree # a copy to permute
> for (i in 1:n){
>  # Pick the first node from the tree
>  a.node<-as.numeric(sample(ptree$node,1))
>  a.node <- 2 # testing
>
>  # This creates a subtree to sample the second branch from
>  extract.a<-extract.clade(ptree,node=as.character(a.node))
>  drop.a.node<-drop.tip(ptree,extract.a$tip.label, trim.internal=F) #trim F
> to leave a place to attach other subtree
>  plot(extract.a, show.node.label = TRUE)
>  plot(drop.a.node, show.node.label = TRUE)
>
>  # Pick a node from somewhere ealse in the tree
>  b.node<-as.numeric(sample(drop.a.node$node,1))
>  b.node <- 5 #testing
>
>  # This creates a subtree to sample the second branch from
>  extract.b<-extract.clade(drop.a.node,node=as.character(b.node))
>  drop.b.node<-drop.tip(drop.a.node,extract.b$tip.label, trim.internal=F)
>  plot(extract.b, show.node.label = TRUE)
>  plot(drop.b.node, show.node.label = TRUE)
>
>  #   drop.b.node contains whatever is left after clipping out the two
> subtrees
>  #   now I want to reassemble the tree switching extract.a and extract.b
>  bind.tree.1<-bind.tree(drop.b.node,extract.a,where=b.node) # doesnt work?
>  plot(bind.tree.1, show.node.label = TRUE)
>  bind.tree.2<-bind.tree(bind.tree.1,extract.b,where=a.node)
>  plot(bind.tree.2, show.node.label = TRUE)
>  #copy the results
>  ptree <- bind.tree.2
>  }
>
> #plot the permuted tree
> plot(ptree, show.node.label = TRUE)
>
> #END
>
>
> *
> Sean S. Downey, Ph.D.
> Institute of Archaeology
> University College London
> 31-34 Gordon Square
> London
> WC1H 0PY
> s.dow...@ucl.ac.uk
> http://www.homepages.ucl.ac.uk/~tcrnssd/
> UK Cell: +44 (0)7542 41 0077
> Belize Cell: +501 636-2939
>
> ___
> R-sig-phylo mailing list
> R-sig-phylo@r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
>



-- 
Rob Lanfear
Research Fellow,
Ecology, Evolution, and Genetics,
Research School of Biology,
Australian National University

Tel: +61 2 6125 4321
www.robertlanfear.com

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[R-sig-phylo] Function that could give me the last node shared by two communities.

[Franciele Parreira Peixoto]

Hello,I am working with a phylogenetic beta diversity index (phylosor) that 
measures the amount of shared phylogenetic history (shared branches) between 
two communities. Furthermore I would like information about the separated time 
between the communities. I am looking for a function that could give me the 
last node shared by two communities. I need  to know when (what node) they stop 
sharing nodes. 
Anyone can help me?
Thanks,
Fran_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ ^0^ _ ^0^_^0^ Franciele 
Parreira Peixoto, Msc student.Graduate Program in Ecology and Evolution

Applied Ecology & Conservation LabDepartment of Ecology, Universidade Federal 
de Goiás - BrazilCV:   http://lattes.cnpq.br/3270814551206587Lab: 
http://www.wix.com/aeclab/leac?ref=nf#!Skype: fran.parreira.peixoto



  
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Re: [R-sig-phylo] Alternative to rapply() for nested lists of phylo objects?

[Rich FitzJohn]

Hi Dave,

I believe that this does what you want ('d'apply for Dave).

dapply <- function(obj, FUN, class="phylo", default=NULL) {
  ret <- lapply(obj, function(x)
if (inherits(x, class)) FUN(x)
else if (is.atomic(x)) default
else dapply(x, FUN, class))
  names(ret) <- names(obj)
  ret
}

library(ape)
tree<-rtree(10)
## Named lists to check that things are where they should be.
list1<-list(a=tree,b=tree,c=tree)
list2<-list(e=list1,f=tree,g=list1)
dapply(list2, Ntip)

Basically this recursively applies maps itself over lists until it hits an 
object of class 'class' ("phylo" by default).  If it never finds an element of 
that class by the time it reaches an atomic class (e.g., numeric) it will 
return default (by default NULL):

list3<-list(e=list1,f=tree,g=list1,h=NA)
dapply(list3,Ntip)

The above function won't be a good idea in all cases, and isn't much tested, 
etc, etc.  This also doesn't preserve class attributes, of the component lists, 
but that could be done in the same way as names() is.

Cheers,
Rich

On 2012-03-14, at 2:39 PM, David Bapst wrote:

> Hello all,
> I am dealing with simulation results that produce nested lists of trees
> (with unbalanced depths; i.e. the first list might have five lists of three
> trees, the second element might have three lists of five trees, the third
> element might just be a single tree). I want to do some analyses on each of
> these trees, so one option would be flattening the list and recording their
> original position in the list. Alternatively, I'd prefer to retain the
> structure of the nested list. I recently discovered rapply() and thought
> this was a perfect fix, only to discover that it appears to look at the
> type() and not the class() of objects passed to it, so it ignores the phylo
> objects as a whole and passes right on to their constituent elements.
> 
> For example:
> 
> library(ape)
> tree<-rtree(10)
> list1<-list(tree,tree,tree)
> list2<-list(list1,tree,list1)
> rapply(list2,Ntip)
> 
> Playing with arguments in rapply doesn't stop this behavior; indeed, it
> seems nothing will stop rapply from ignoring the type 'list' of the phylo
> objects themselves. Does anyone know of an alternative to rapply that
> considers the class of the nested objects instead?
> 
> Thanks,
> -Dave B.
> 
> -- 
> David Bapst
> Dept of Geophysical Sciences
> University of Chicago
> 5734 S. Ellis
> Chicago, IL 60637
> http://home.uchicago.edu/~dwbapst/
> http://cran.r-project.org/web/packages/paleotree/index.html
> 
> 
> 
>   [[alternative HTML version deleted]]
> 
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Re: [R-sig-phylo] Alternative to rapply() for nested lists of phylo objects?

[David Bapst]

Ooh, thanks Rich for this truly dapper 'dapply' function! Works like a
charm.
-Dave

On Wed, Mar 14, 2012 at 7:42 PM, Rich FitzJohn wrote:

> Hi Dave,
>
> I believe that this does what you want ('d'apply for Dave).
>
> dapply <- function(obj, FUN, class="phylo", default=NULL) {
>  ret <- lapply(obj, function(x)
>if (inherits(x, class)) FUN(x)
>else if (is.atomic(x)) default
>else dapply(x, FUN, class))
>  names(ret) <- names(obj)
>  ret
> }
>
> library(ape)
> tree<-rtree(10)
> ## Named lists to check that things are where they should be.
> list1<-list(a=tree,b=tree,c=tree)
> list2<-list(e=list1,f=tree,g=list1)
> dapply(list2, Ntip)
>
> Basically this recursively applies maps itself over lists until it hits an
> object of class 'class' ("phylo" by default).  If it never finds an element
> of that class by the time it reaches an atomic class (e.g., numeric) it
> will return default (by default NULL):
>
> list3<-list(e=list1,f=tree,g=list1,h=NA)
> dapply(list3,Ntip)
>
> The above function won't be a good idea in all cases, and isn't much
> tested, etc, etc.  This also doesn't preserve class attributes, of the
> component lists, but that could be done in the same way as names() is.
>
> Cheers,
> Rich
>
> On 2012-03-14, at 2:39 PM, David Bapst wrote:
>
> > Hello all,
> > I am dealing with simulation results that produce nested lists of trees
> > (with unbalanced depths; i.e. the first list might have five lists of
> three
> > trees, the second element might have three lists of five trees, the third
> > element might just be a single tree). I want to do some analyses on each
> of
> > these trees, so one option would be flattening the list and recording
> their
> > original position in the list. Alternatively, I'd prefer to retain the
> > structure of the nested list. I recently discovered rapply() and thought
> > this was a perfect fix, only to discover that it appears to look at the
> > type() and not the class() of objects passed to it, so it ignores the
> phylo
> > objects as a whole and passes right on to their constituent elements.
> >
> > For example:
> >
> > library(ape)
> > tree<-rtree(10)
> > list1<-list(tree,tree,tree)
> > list2<-list(list1,tree,list1)
> > rapply(list2,Ntip)
> >
> > Playing with arguments in rapply doesn't stop this behavior; indeed, it
> > seems nothing will stop rapply from ignoring the type 'list' of the phylo
> > objects themselves. Does anyone know of an alternative to rapply that
> > considers the class of the nested objects instead?
> >
> > Thanks,
> > -Dave B.
> >
> > --
> > David Bapst
> > Dept of Geophysical Sciences
> > University of Chicago
> > 5734 S. Ellis
> > Chicago, IL 60637
> > http://home.uchicago.edu/~dwbapst/
> > http://cran.r-project.org/web/packages/paleotree/index.html
> >
> > 
> >
> >   [[alternative HTML version deleted]]
> >
> > ___
> > R-sig-phylo mailing list
> > R-sig-phylo@r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
>
> ___
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> https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
>



-- 
David Bapst
Dept of Geophysical Sciences
University of Chicago
5734 S. Ellis
Chicago, IL 60637
http://home.uchicago.edu/~dwbapst/
http://cran.r-project.org/web/packages/paleotree/index.html

 

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[R-sig-phylo] Testing for phylogenetic signal in proportions

[Rob Lanfear]

Hi All,

I've tried searching the literature for this but the search terms tend to
give irrelevant papers, so I thought I'd ask for some guidance here.

I have a set of 11 species, an ultrametric tree for the species, and for
each species I have a set of proportional data for 5 chemical traits. E.g.
for spp1 my data might be: chemicalA=10%, chemicalB=50%, chemicalC=1%,
chemicalD=19%, chemicalE=20%. The set of traits for each species always
sums to 100%, but I don't know, and can't measure, the absolute values of
the traits. Biologically speaking, this is OK, because it's the proportions
that I'm interested in.

I want to test for phylogenetic signal in these traits, and estimate the
rate of change of each proportion along the phylogeny. Can anyone point me
to any appropriate references for the methods and pitfalls of attempting to
do this with proportion data? I can see that proportional data will have
some odd properties (non-independence of traits, bounded (i.e.
non-Brownian) evolution, etc.), but the best way of accounting for these is
not immediately apparent to me.

Thanks,

Rob

-- 
Rob Lanfear
Research Fellow,
Ecology, Evolution, and Genetics,
Research School of Biology,
Australian National University

Tel: +61 2 6125 4321
www.robertlanfear.com

[[alternative HTML version deleted]]

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Re: [R-sig-phylo] Testing for phylogenetic signal in proportions

[Theodore Garland Jr]

It is really too few species to have a sufficiently powerful test for 
phylogenetic signal.  See Blomberg et al. (2003), available on my website.

Cheers,
Ted

Theodore Garland, Jr.
Professor
Department of Biology
University of California, Riverside
Riverside, CA 92521
Office Phone:  (951) 827-3524
Wet Lab Phone:  (951) 827-5724
Dry Lab Phone:  (951) 827-4026
Home Phone:  (951) 328-0820
Facsimile:  (951) 827-4286 = Dept. office (not confidential)
Email:  tgarl...@ucr.edu
http://www.biology.ucr.edu/people/faculty/Garland.html

Experimental Evolution: Concepts, Methods, and Applications of Selection 
Experiments. 2009.
Edited by Theodore Garland, Jr. and Michael R. Rose
http://www.ucpress.edu/book.php?isbn=9780520261808
(PDFs of chapters are available from me or from the individual authors)


From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org] on 
behalf of Rob Lanfear [rob.lanf...@gmail.com]
Sent: Wednesday, March 14, 2012 8:18 PM
To: r-sig-phylo
Subject: [R-sig-phylo] Testing for phylogenetic signal in proportions

Hi All,

I've tried searching the literature for this but the search terms tend to
give irrelevant papers, so I thought I'd ask for some guidance here.

I have a set of 11 species, an ultrametric tree for the species, and for
each species I have a set of proportional data for 5 chemical traits. E.g.
for spp1 my data might be: chemicalA=10%, chemicalB=50%, chemicalC=1%,
chemicalD=19%, chemicalE=20%. The set of traits for each species always
sums to 100%, but I don't know, and can't measure, the absolute values of
the traits. Biologically speaking, this is OK, because it's the proportions
that I'm interested in.

I want to test for phylogenetic signal in these traits, and estimate the
rate of change of each proportion along the phylogeny. Can anyone point me
to any appropriate references for the methods and pitfalls of attempting to
do this with proportion data? I can see that proportional data will have
some odd properties (non-independence of traits, bounded (i.e.
non-Brownian) evolution, etc.), but the best way of accounting for these is
not immediately apparent to me.

Thanks,

Rob

--
Rob Lanfear
Research Fellow,
Ecology, Evolution, and Genetics,
Research School of Biology,
Australian National University

Tel: +61 2 6125 4321
www.robertlanfear.com

[[alternative HTML version deleted]]

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Re: [R-sig-phylo] Testing for phylogenetic signal in proportions

[Rob Lanfear]

Hi Ted,

Thanks for the pointer - I wasn't aware of that paper.

Phylogenetic signal might be out, but do you (or others) think it would be
possible to compare rates of change in the proportions. For instance, a
striking pattern in the data is that one of the proportions remains almost
constant across species, while others vary a great deal.

I had in mind that one way to statistically compare these would be to
estimate rates of change (with an appropriate model) for each trait, and
then to test for differences in rates of change by fixing rates for a given
trait to the ML rate for each of the other traits, and comparing
likelihoods with a likelihood ratio test.

That might be overkill on the data, given that the sample size is small and
the pattern is pretty obvious visually, but it would be nice to know under
some reasonable null model whether the differences we see could have arisen
by chance.

Does something like that sound plausible?

Rob

On 15 March 2012 14:23, Theodore Garland Jr wrote:

> It is really too few species to have a sufficiently powerful test for
> phylogenetic signal.  See Blomberg et al. (2003), available on my website.
>
> Cheers,
> Ted
>
> Theodore Garland, Jr.
> Professor
> Department of Biology
> University of California, Riverside
> Riverside, CA 92521
> Office Phone:  (951) 827-3524
> Wet Lab Phone:  (951) 827-5724
> Dry Lab Phone:  (951) 827-4026
> Home Phone:  (951) 328-0820
> Facsimile:  (951) 827-4286 = Dept. office (not confidential)
> Email:  tgarl...@ucr.edu
> http://www.biology.ucr.edu/people/faculty/Garland.html
>
> Experimental Evolution: Concepts, Methods, and Applications of Selection
> Experiments. 2009.
> Edited by Theodore Garland, Jr. and Michael R. Rose
> http://www.ucpress.edu/book.php?isbn=9780520261808
> (PDFs of chapters are available from me or from the individual authors)
>
> 
> From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org]
> on behalf of Rob Lanfear [rob.lanf...@gmail.com]
> Sent: Wednesday, March 14, 2012 8:18 PM
> To: r-sig-phylo
> Subject: [R-sig-phylo] Testing for phylogenetic signal in proportions
>
> Hi All,
>
> I've tried searching the literature for this but the search terms tend to
> give irrelevant papers, so I thought I'd ask for some guidance here.
>
> I have a set of 11 species, an ultrametric tree for the species, and for
> each species I have a set of proportional data for 5 chemical traits. E.g.
> for spp1 my data might be: chemicalA=10%, chemicalB=50%, chemicalC=1%,
> chemicalD=19%, chemicalE=20%. The set of traits for each species always
> sums to 100%, but I don't know, and can't measure, the absolute values of
> the traits. Biologically speaking, this is OK, because it's the proportions
> that I'm interested in.
>
> I want to test for phylogenetic signal in these traits, and estimate the
> rate of change of each proportion along the phylogeny. Can anyone point me
> to any appropriate references for the methods and pitfalls of attempting to
> do this with proportion data? I can see that proportional data will have
> some odd properties (non-independence of traits, bounded (i.e.
> non-Brownian) evolution, etc.), but the best way of accounting for these is
> not immediately apparent to me.
>
> Thanks,
>
> Rob
>
> --
> Rob Lanfear
> Research Fellow,
> Ecology, Evolution, and Genetics,
> Research School of Biology,
> Australian National University
>
> Tel: +61 2 6125 4321
> www.robertlanfear.com
>
> [[alternative HTML version deleted]]
>
> ___
> R-sig-phylo mailing list
> R-sig-phylo@r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
>



-- 
Rob Lanfear
Research Fellow,
Ecology, Evolution, and Genetics,
Research School of Biology,
Australian National University

Tel: +61 2 6125 4321
www.robertlanfear.com

[[alternative HTML version deleted]]

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Re: [R-sig-phylo] Testing for phylogenetic signal in proportions

[Emmanuel Paradis]

Hi Rob,

You may try ppca() in adephylo. A "test" of phylogenetic signal is given by the 
sign of the eigenvalues.

Cheers,

Emmanuel
-Original Message-
From: Rob Lanfear 
Sender: r-sig-phylo-boun...@r-project.org
Date: Thu, 15 Mar 2012 15:54:29 
To: Theodore Garland Jr
Cc: r-sig-phylo
Subject: Re: [R-sig-phylo] Testing for phylogenetic signal in proportions

Hi Ted,

Thanks for the pointer - I wasn't aware of that paper.

Phylogenetic signal might be out, but do you (or others) think it would be
possible to compare rates of change in the proportions. For instance, a
striking pattern in the data is that one of the proportions remains almost
constant across species, while others vary a great deal.

I had in mind that one way to statistically compare these would be to
estimate rates of change (with an appropriate model) for each trait, and
then to test for differences in rates of change by fixing rates for a given
trait to the ML rate for each of the other traits, and comparing
likelihoods with a likelihood ratio test.

That might be overkill on the data, given that the sample size is small and
the pattern is pretty obvious visually, but it would be nice to know under
some reasonable null model whether the differences we see could have arisen
by chance.

Does something like that sound plausible?

Rob

On 15 March 2012 14:23, Theodore Garland Jr wrote:

> It is really too few species to have a sufficiently powerful test for
> phylogenetic signal.  See Blomberg et al. (2003), available on my website.
>
> Cheers,
> Ted
>
> Theodore Garland, Jr.
> Professor
> Department of Biology
> University of California, Riverside
> Riverside, CA 92521
> Office Phone:  (951) 827-3524
> Wet Lab Phone:  (951) 827-5724
> Dry Lab Phone:  (951) 827-4026
> Home Phone:  (951) 328-0820
> Facsimile:  (951) 827-4286 = Dept. office (not confidential)
> Email:  tgarl...@ucr.edu
> http://www.biology.ucr.edu/people/faculty/Garland.html
>
> Experimental Evolution: Concepts, Methods, and Applications of Selection
> Experiments. 2009.
> Edited by Theodore Garland, Jr. and Michael R. Rose
> http://www.ucpress.edu/book.php?isbn=9780520261808
> (PDFs of chapters are available from me or from the individual authors)
>
> 
> From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org]
> on behalf of Rob Lanfear [rob.lanf...@gmail.com]
> Sent: Wednesday, March 14, 2012 8:18 PM
> To: r-sig-phylo
> Subject: [R-sig-phylo] Testing for phylogenetic signal in proportions
>
> Hi All,
>
> I've tried searching the literature for this but the search terms tend to
> give irrelevant papers, so I thought I'd ask for some guidance here.
>
> I have a set of 11 species, an ultrametric tree for the species, and for
> each species I have a set of proportional data for 5 chemical traits. E.g.
> for spp1 my data might be: chemicalA=10%, chemicalB=50%, chemicalC=1%,
> chemicalD=19%, chemicalE=20%. The set of traits for each species always
> sums to 100%, but I don't know, and can't measure, the absolute values of
> the traits. Biologically speaking, this is OK, because it's the proportions
> that I'm interested in.
>
> I want to test for phylogenetic signal in these traits, and estimate the
> rate of change of each proportion along the phylogeny. Can anyone point me
> to any appropriate references for the methods and pitfalls of attempting to
> do this with proportion data? I can see that proportional data will have
> some odd properties (non-independence of traits, bounded (i.e.
> non-Brownian) evolution, etc.), but the best way of accounting for these is
> not immediately apparent to me.
>
> Thanks,
>
> Rob
>
> --
> Rob Lanfear
> Research Fellow,
> Ecology, Evolution, and Genetics,
> Research School of Biology,
> Australian National University
>
> Tel: +61 2 6125 4321
> www.robertlanfear.com
>
> [[alternative HTML version deleted]]
>
> ___
> R-sig-phylo mailing list
> R-sig-phylo@r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
>



-- 
Rob Lanfear
Research Fellow,
Ecology, Evolution, and Genetics,
Research School of Biology,
Australian National University

Tel: +61 2 6125 4321
www.robertlanfear.com

[[alternative HTML version deleted]]

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