Re: [MORPHMET] Dennis Slice

2019-06-17 Thread Carmelo Fruciano
This is extremely sad news. He has made enormous contributions to our 
field and his figure will be greatly missed. I have had limited 
interactions with him but, based on the interactions I had the privilege 
to have, I also concur with Mauro Cavalcanti that he had a nice sense of 
humor.

My most heartfelt condolences to his family, his friends, and all our field.
Carmelo


--


==
Carmelo Fruciano
Institute of Biology
Ecole Normale Superieure - Paris
CNRS
http://www.fruciano.it/research/


On 15/06/2019 16:55, mitte...@univie.ac.at wrote:

      Dear subscribers to morphmet,

      With the deepest grief we must inform you of the sudden
  death on June 13 of Prof. Dennis E. Slice,
  holder of the fourth Rohlf Award for Excellence in Morphometrics
  and tireless founder and moderator of this newsgroup,
  who suffered a heart attack in his home town of
  Tallahassee, Florida. Morphometrics will not be the same
  without him.

 Jim Rohlf, Fred Bookstein, Paul O'Higgins,
   Benedikt Hallgrimsson, June 15, 2019

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Re: [MORPHMET] morph disparity

2018-11-19 Thread Carmelo Fruciano

Hi,
it's hard to give clear answers as context is missing. But I will try to 
give my general opinion on this.


If you had some a priori idea of meaningful shape variation and you were 
sure this variation is represented by an individual PC axis (and that 
axis only), it would be sensible to make that computation for that axis.
However, in your case - and in most cases where a similar question is 
posed - this doesn't seem to apply (i.e., from the way you ask the 
question, it sounds like you want to compute variance for each of the 
axes separately simply because PCA gives you a set of orthogonal axes). 
Then - provided that I don't know enough about your 
system/question/analysis and this is just a general opinion - I would 
just stick to multivariate measures of variation.


I hope this helps.
Carmelo



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Institute of Biology
Ecole Normale Superieure - Paris
CNRS
http://www.fruciano.it/research/


On 16/11/2018 19:45, colymboides wrote:

Hi everyone,

I extracted Procrustes shape variables describing 95% of the variation 
(PC1-PC4) in my data and plotted shape changes in morphospace. By 
plotting the warps I know what shape changes are described along each PC 
axis. For example, PC1 describes elongated (PC1 min) to stout (PC1 max) 
shapes. Would it be sensible to calculate some measure of variance/morph 
disparity among my species using the PC scores for each PC axis (e.g. 
compare species X PC1 to species Y PC1) as opposed to calculating 
disparity by using combined PC axes?


Nick

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Re: [MORPHMET] A question regarding "target shape"

2018-11-06 Thread Carmelo Fruciano




On 05/11/2018 18:50, Diego Ardón wrote:

Captura de pantalla 2018-11-05 a la(s) 11.40.26.png


Thank you Mr. Fruciano. I had already made the DFA, but wasn't aware the 
graphical output represented both groups (it certainly makes sense). I 
have a couple of other questions regarding semi-landmarks. I probably 
should start a new topic, but I'll first try out here:



So, I was adviced to use semi-landmarks, I placed them with MakeFan8, 
saved the files as images and then used TpsDig to place all landmarks, 
however I didn't make any distinctions between landmarks and 
semi-landmarks. What unsettles me is (1) that I've recently comed across 
the term "sliding semi-landmarks", which leads me to believe 
semi-landmarks should behave in a particular way.


Well, it's a long topic, but the general idea is that, to account for 
the uncertainty in placement of a semilandmark along a curve, this is 
slid along the curve itself (or, more frequently, its approximation) so 
that ideally only variation perpendicular to the curve (reflecting the 
curvature) is retained.
In current practice, semilandmarks are slid. Various software can do 
this, the most popular for 2D data being certainly tpsRelW by F.J. Rohlf.

A good, recent and accessible treatment of this topic is:

Gunz & Mitteroecker 2013. Semilandmarks: a method for quantifying curves 
and surfaces. Hystrix



The second thing that 
unsettles me is whether "more semi-landmarks" means a better analysis.


Not necessarily.

I 
can understand that most people wouldn't use 65 landmarks+semilandmarks 
because it's a painstaking job to digitize them, however, in my recent 
reads I've comed across concepts like a "Variables to specimen ratio", 
which one paper suggested specimens should be 5 times the number of 
variables. I do have a a data set of nearly 400 specimens, but it does 
come short if indeed I should have 65*2*5 specimens!


There are two issues: 1. whether statistical procedures are defined, 2. 
whether one has enough power and/or how large is error in estimates.


The first issue is easy to deal with: certain statistical procedures 
(for instance, the ones involving matrix inversion) are not defined if 
there are many variables and relatively few cases. These procedures 
simply "don't work". However, there are other alternative procedures 
which do work (e.g., the ones based on distances) and/or workarounds 
(e.g., use of generalized inverses).


The second issue is much more complex and I doubt one can give a 
straightforward answer. In general, the more observations (specimens) 
the better (when one can get them, that is). But the idea of a certain 
number of observations relative to the number of variables is, at best, 
a rule of thumb.


Clearly, having too many variables can create problems and artifacts. An 
interesting recent example of this can be found in


Bookstein 2016 - A newly noticed formula enforces fundamental limits of 
geometric morphometric analyses. Evolutionary Biology


In your particular case, if I were you I would ask myself whether all 
those points/semilandmarks are that necessary to capture biologically 
relevant variation. That is a question that only you can answer, based 
on your knowledge of the biological problem at hand.


Statistical power and reliability of estimates is another issue, which 
is in part dataset-dependent (as well as dependent on which statistical 
procedures you intend to use). An interesting paper dealing with this is


Cardini 2007. Sample size and sampling error in geometric morphometric 
studies of size and shape. Zoomorphology


In general, as said above, it's very hard to give straightforward 
answers to your question.

I hope this still helps, though.
Carmelo


==
Carmelo Fruciano
Institute of Biology
Ecole Normale Superieure - Paris
CNRS
http://www.fruciano.it/research/


El lunes, 5 de noviembre de 2018, 2:12:20 (UTC-6), Carmelo Fruciano 
escribió:




On 03/11/2018 22:28, Diego Ardón wrote:
 > Dear Mr. Soda,
 >
 > Thank you for replying. Your statement " setting one group’s mean
shape
 > to be the starting shape and the other group’s to the target;
this will
 > lead to the most direct comparison. " pretty much describes what
I have
 > in mind to do. Which software could I use to do this? since I
believe
 > MorphoJ will not do it.

Dear Diego,
MorphoJ will actually do it. The easiest is to use what is under the
menu "Discriminant analysis". MorphoJ's user guide has a brief but very
clear description of the graphical output.
I hope this helps.
Best,
Carmelo


-- 



==
Carmelo Fruciano
Institute of Biology
Ecole Normale Superieure - Paris
CNRS
http://www.fruciano.it/research/ <http://www.fruciano.it/research/>


 > El miércoles, 31 de octu

Re: [MORPHMET] A question regarding "target shape"

2018-11-05 Thread Carmelo Fruciano




On 03/11/2018 22:28, Diego Ardón wrote:

Dear Mr. Soda,

Thank you for replying. Your statement " setting one group’s mean shape 
to be the starting shape and the other group’s to the target; this will 
lead to the most direct comparison. " pretty much describes what I have 
in mind to do. Which software could I use to do this? since I believe 
MorphoJ will not do it.


Dear Diego,
MorphoJ will actually do it. The easiest is to use what is under the 
menu "Discriminant analysis". MorphoJ's user guide has a brief but very 
clear description of the graphical output.

I hope this helps.
Best,
Carmelo


--


======
Carmelo Fruciano
Institute of Biology
Ecole Normale Superieure - Paris
CNRS
http://www.fruciano.it/research/


El miércoles, 31 de octubre de 2018, 13:51:07 (UTC-6), K. James Soda 
escribió:


Dear Mr. Ardón,

Good question. Whenever we make shape comparisons in GM, be that via
displacement vector or deformation grid (which is what you’re
doing), we can typically only compare two shapes at a time. One
shape is called the reference (or starting shape, in this case).
This is the shape for which the grid would look “normal”; straight,
equally spaced grid lines. The second is the target, where the grid
is deformed to take this second configuration. If you want to
compare two geographic groups, I would suggest setting one group’s
mean shape to be the starting shape and the other group’s to the
target; this will lead to the most direct comparison. I am not
certain how easy this is to do in MorphoJ, though.

Hope this helps,

James

On Oct 31, 2018, at 12:01 PM, Diego Ardón > wrote:


Hello, my name is Diego and I'm currently undertaking a Master's
program in Mexico. One of my thesis project involves a geometric
morphometrics study on the shape of a freshwater fish which
distributes across Central America. I'm currently having trouble
with a concept that will probably be very simple to most of you,
but which I haven't found a way to get my head around.

I'm running a CVA on MorphoJ, dividing my dataset into two
geographically distinct groups. I run the test and change the type
of graph to a "Warped Outline Drawing". So now the graph is
showing a "starting shape" which I interpret as it being the
average of all my landmark data (both geographical groupings),
however I'm not sure on how to interpret the "target shape". I was
expecting to have two "target shapes", one for each of the
geographical groupings. Could someone please help point out my
misunderstanding and offer me a way on how to interpret the
"target shape"?

Thank you, I'll be very thankful

Diego Ardón

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Re: [MORPHMET] Problem to export data from Landmak editor to MorphoJ

2018-10-11 Thread Carmelo Fruciano

Dear Maria,
I will complement the excellent answer given by Murat by saying that you 
can use Morpho also to import dta files produced by Landmark Editor 
using the function read.lmdta (thus avoiding using read.table)
The code below should do the trick of converting a dta file for use in 
MorphoJ


library(Morpho)

Data=read.lmdta(file="YOURFILENAME.dta")
# Import dta file
r2morphoj(Data$arr, file="Data.txt")
# Export in a format compatible with MorphoJ

I hope this helps,
Carmelo


On 09/10/2018 21:27, Maria Gracia Salamanca Garcia wrote:

Dear morphometricians,


I am doing geometric morphometric analysis to 3D scans (more than 100 scans), 
and I am using Landmark Editor. I have already placed all the landmarks in the 
same order and did all the correspondences.

However, I am unable to export the data to MorphoJ. The software shows me a 
window that says 'The selected measures have inconsistent correspondences to 
the atlas', and then collapses.

I redid all the correspondences, tried different arrangements, but it keeps 
failing.

I am trying to export from ply to NTsys file.

Does someone knows how to fix this error or which is my mistake?

Thank you very much!



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Institute of Biology
Ecole Normale Superieure - Paris
CNRS
http://www.fruciano.it/research/

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Re: [MORPHMET] How to obtain measurements from 3D scans

2018-09-10 Thread Carmelo Fruciano




On 10/09/2018 03:06, Pablo Fisichella wrote:

Dear morphometricians

I am interested to obtain linear measurements from 3D models of human 
fossil teeth.


Dear Paolo,
in addition to the very informative reply by Murat, I have a couple of 
further suggestions/alternatives



Given that I don’t have more access to the fossils now I 
am planning to use the 3D length tool in Avizo to obtain the 
measurements that I need.


Another option could simply be to collect points (that is 
(semi)landmarks) on the tooth and then compute linear distances among 
them using their XYZ coordinates. If you have a substantial number of 
measurement and some proficiency in R/Matlab/similar, this might be 
faster (and easier to retrieve in the future what you have done).


My question is if the measurements obtained 
from the 3D models are a good proxy of those obtained directly from 
fossil teeth using a caliper and if such 3D measurements can be actually 
used to perform statistical analyses.


If you had access to caliper measurements on the same specimens (or a 
subset), you could also test for this rather than relying on expert 
opinions. See:


Arnqvist G, Mårtensson T. 1998. Measurement error in geometric 
morphometrics: empirical strategies to assess and reduce its impact on 
measures of shape. Acta Zoologica Academiae Scientiarum Hungaricae 44:73-96.


Fruciano C. 2016. Measurement error in geometric morphometrics. 
Development Genes and Evolution 226:139-158.


In addition, I need to perform 2D 
geometric morphometric analyses in some teeth (molars) where the use of 
3D landmarks/semilandmarks is not very useful. So, I want to know if 
there exists a way to obtain standardized 2D pictures using Avizo or 
another software which can be used to carry out 2D GM analyses.


One thing that you may try if you can place some points to define your 
plane in a reliable fashion as the two main axes is to perform a 
principal component analysis (on the covariance matrix) using each 
individual point as observation and x,y,z as variables, then retain the 
first two principal components (eigenvectors), center (using the mean of 
the points mentioned above) and project your true (semi)landmarks onto 
these two principal components. If most of the variation in your true 
(semi)landmarks is already along the two directions which identify your 
plane of interest, you might even do this in a single step (i.e., 
perform a PCA for each individual using points as observations, x,y,z as 
variables and then retain the scores along the first two principal 
components for 2D geometric morphometric analyses).


Obviously, you'd still have the potential issue with projection of a 3D 
structure on a 2D plane. For that, in addition to my review cited above, 
you might want to check


Cardini A. 2014. Missing the third dimension in geometric morphometrics: 
how to assess if 2D images really are a good proxy for 3D structures? 
Hystrix, the Italian Journal of Mammalogy 25:73-81.


This paper suggest an approach you can use to quantify how well your 2D 
data approximate the 3D data. As you would have both, it could be a good 
way to check whether the projection you are choosing gives you 
appropriate results.


I hope this helps,
Carmelo


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==
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Ecole Normale Superieure - Paris
CNRS
http://www.fruciano.it/research/

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Re: [MORPHMET] digit.curves

2018-08-13 Thread Carmelo Fruciano




On 12/08/2018 22:20, Ian F wrote:
Does digit.curves require data in long on wide format? when i try to use 
it i get the error


  "  Error in digit.curves(2880, Rafalt1, nPoints = 30, closed=TRUE):
   Input must be a p-x-k matrix of curve coordinates"

what is a p-x-k matrix. I have searched it on the internet and have come 
up with nothing.I have tried both long and wide format and have had the 
same result. any help is much appreciated.


I'm not going to go into the details of the specific function call. But 
p by x by k is normally called a (3D) array in R. It's like a "stack of 
matrices" on a third dimension.
If you do a google search for "3D arrays R" (without quote), you'll find 
plenty of stuff to understand how it works, such as

http://aaronlichtner.com/r-a-little-bit-on-multidimensional-arrays-and-apply/
https://www.dummies.com/programming/r/how-to-create-an-array-in-r/
I hope this helps.
Carmelo

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Re: [MORPHMET] Re: Trouble with 2-D morphomeric analysis in geomorph

2018-08-09 Thread Carmelo Fruciano

Dear Ian,
it sounds more like an R data manipulation issue (which admittedly can 
be a pain) than a morphometric issue.
Basically you want to convert from a "long" format to a "wide" format. 
You can read about this in multiple places on the internet, such as

http://www.cookbook-r.com/Manipulating_data/Converting_data_between_wide_and_long_format/
https://www.statmethods.net/management/reshape.html

I have tried my hand on your data, see code below. I'm sure there are 
1000 other ways you can do this, including in a more elegant fashion...
But in general what I did is to create some indexing variables for 
specimen and landmark and used them to restructure the data.


I hope this helps,
Carmelo


--


======
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Institute of Biology
Ecole Normale Superieure - Paris
CNRS
http://www.fruciano.it/research/




##
##

data <- read.table("Trial2rawcoords.txt", header=TRUE)
# Import data

landmarks=30
# Number of landmarks

data$specimen=as.factor(unlist(lapply(seq_len(landmarks), function(x) 
rep(seq_len(landmarks)[x],30

data$landmark=as.factor(rep(1:30,30))
# Create two factors to index the various x,y coordinates

library(reshape)
data_wide=reshape(data,
   idvar = "specimen",
   timevar = "landmark",
   direction = "wide")
# Use reshape to convert from long to wide format

landmarknames=unlist(lapply(seq_len(landmarks), function(x) 
c(paste("x.",x,sep=""),paste("y.",x,sep=""

# Create ad hoc names to use for indexing

data_wide=cbind(data_wide$specimen,data_wide$genus.1,data_wide[,landmarknames])
# Get only the useful columns

##
##




On 09/08/2018 01:53, Ian F wrote:
I figured out what the issue was. thank you for your help. regrettably I 
have encountered another issue, any insight  would be much appreciated. 
I am trying to reformat a spreadsheet so that each individual is a row 
and each column represents an x or y coordinate. my data set consists of 
30 specimens each with 30 landmarks. I keep getting the error code  
Error in `[<-`(`*tmp*`, j, 1, value = sub.data[1, 1]) :

   subscript out of bounds.

My data is in the link and my code is as follows.


# reformat data from imageJ into R compatible format.

data <- read.table(Trial2rawcoords.txt, header=TRUE)

len <- length(data$X)
overall.table <- matrix(nrow=len/30, ncol=(30*2)+1)
overall.length <- len/30
for(j in c(1:overall.length)) {
print(j)

sub.data <- as.matrix(data[ (1+30*(j-1)):((1+30*(j-1))+29), 2:4])

overall.table[j,1] <- sub.data[1, 1]
overall.table[j,2:3] <- sub.data[1, 2:3]
overall.table[j,4:5] <- sub.data[2, 2:3]
overall.table[j,6:7] <- sub.data[3, 2:3]
overall.table[j,8:9] <- sub.data[4, 2:3]
overall.table[j,10:11] <- sub.data[5, 2:3]
overall.table[j,12:13] <- sub.data[6, 2:3]
overall.table[j,14:15] <- sub.data[7, 2:3]
overall.table[j,16:17] <- sub.data[8, 2:3]
overall.table[j,18:19] <- sub.data[9, 2:3]
overall.table[j,20:21] <- sub.data[10, 2:3]
overall.table[j,22:23] <- sub.data[11, 2:3]
overall.table[j,24:25] <- sub.data[12, 2:3]
overall.table[j,26:27] <- sub.data[13, 2:3]
overall.table[j,28:29] <- sub.data[14, 2:3]
overall.table[j,30:31] <- sub.data[15, 2:3]
overall.table[j,32:33] <- sub.data[16, 2:3]
overall.table[j,34:35] <- sub.data[17, 2:3]
overall.table[j,36:37] <- sub.data[18, 2:3]
overall.table[j,38:39] <- sub.data[19, 2:3]
overall.table[j,40:41] <- sub.data[20, 2:3]
overall.table[j,42:43] <- sub.data[21, 2:3]
overall.table[j,44:45] <- sub.data[22, 2:3]
overall.table[j,46:47] <- sub.data[23, 2:3]
overall.table[j,48:49] <- sub.data[24, 2:3]
overall.table[j,50:51] <- sub.data[25, 2:3]
overall.table[j,52:53] <- sub.data[26, 2:3]
overall.table[j,54:55] <- sub.data[27, 2:3]
overall.table[j,56:57] <- sub.data[28, 2:3]
overall.table[j,58:59] <- sub.data[29, 2:3]
overall.table[j,60:61] <- sub.data[30, 2:3]
   }
# Confirm the above loop worked.

head(overall.table)
tail(overall.table)
# Assign the new table column names and write out the reformatted table 
to the working directory.


colnames(overall.table) <- c("number", "genus", "x1", "y1", "x2", "y2", 
"x3", "y3", "x4", "y4", "x5", "y5", "x6", "y6", "x7", "y7", "x8", "y8", 
"x9", "y9", "x10", "y10", "x11", "y11", "x12", "y12", "x13", "y13", 
"x14", "y14", "x15", "y15", "x16", "y16", "x17", 
"y17","x18","Y18","X19","Y19","

Re: ***SPAM*** [MORPHMET] Extract Classifier from ID string

2018-03-22 Thread Carmelo Fruciano

Hi Nelly,

you're welcome, and sorry for calling you with some other name.

Best,

Carmelo


On 22/03/2018 15:06, Nelly Ndungu wrote:

Thanks Carmelo,
This trick has worked, thanks alot.
Kind Regards,
Nelly Ndungu

On Thu, Mar 22, 2018 at 4:50 PM, Carmelo Fruciano <c.fruci...@unict.it 
<mailto:c.fruci...@unict.it>> wrote:


Dear Bekkym

I'm assuming you actually have a problem with the specimen names
in the file you imported in MorphoJ.

It's hard to know what exactly the problem is with the information
you provide, but I will point out that a trick which may or may
not apply to your specific case is to convert the TPS file into an
NTS file using tpsUtil, specifying the option to use the image
name as names of your observations (i.e., specimens). At that
point, you import the NTS instead of the TPS.

I hope this helps,

Carmelo



On 22/03/2018 14:42, Nelly wrote:

Dear All,

Kindly assist.
I am trying to generate CVA but this is not possible because
initially i didn't ectract classifiers.
This is because my data appeared as numbers from1-70 in morphoj
instead of sample ids that were in the .jpg file.
As shown below i.e 0,1,2,3.79.
Therefore i could not classify.
How can this be corrected so that i have the full names instead
of numbers in the classifier column.


Kindly assist.
Nelly Ndungu
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Re: ***SPAM*** [MORPHMET] Extract Classifier from ID string

2018-03-22 Thread Carmelo Fruciano

Dear Bekkym

I'm assuming you actually have a problem with the specimen names in the 
file you imported in MorphoJ.


It's hard to know what exactly the problem is with the information you 
provide, but I will point out that a trick which may or may not apply to 
your specific case is to convert the TPS file into an NTS file using 
tpsUtil, specifying the option to use the image name as names of your 
observations (i.e., specimens). At that point, you import the NTS 
instead of the TPS.


I hope this helps,

Carmelo



On 22/03/2018 14:42, Nelly wrote:

Dear All,

Kindly assist.
I am trying to generate CVA but this is not possible because initially 
i didn't ectract classifiers.
This is because my data appeared as numbers from1-70 in morphoj 
instead of sample ids that were in the .jpg file.

As shown below i.e 0,1,2,3.79.
Therefore i could not classify.
How can this be corrected so that i have the full names instead of 
numbers in the classifier column.



Kindly assist.
Nelly Ndungu
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Re: [MORPHMET] digitizing very variable leaves

2018-03-15 Thread Carmelo Fruciano

Hi Tina,

The software Shape by Iwata & Ukai is an user friendly option for 
performing elliptic Fourier analysis.


https://academic.oup.com/jhered/article/93/5/384/2187412

http://lbm.ab.a.u-tokyo.ac.jp/~iwata/shape/

Elliptic Fourier analysis is also implemented in NTSYSpc, which is also 
user-friendly.


You probably want to read a bit on the methodology to see if it fits 
what you plan to do and its potential shortcomings.


I hope this helps.

Carmelo




On 15/03/2018 12:14, 'Tina Klenovšek' via MORPHMET wrote:


Thanks to all, Javier, Vincent, William, Joanna and Dr. Rohlf,

my dilemma occurred because some botanists (I work with mammal skulls) 
have asked me to help them evaluate leaf variability of two tree 
species from different localities. So, variability within and among 
individual trees and species.


In which user friendly program (like MorphoJ J) can I analyse outline 
data and visualize variability?


Thank you again,

Tina

*From:*Joanna Lenarczyk [mailto:j.kowal...@botany.pl]
*Sent:* Thursday, March 15, 2018 10:21 AM
*To:* Tina Klenovšek
*Subject:* Re: [MORPHMET] digitizing very variable leaves

Hello Tina,

You can try a program which does not need landmarks:

http://www.eletel.p.lodz.pl/pms/SoftwareQmazda.html

I hope it will help you :) I have not tried it yet by myself, but it 
can be useful when you cannot or do not want use landmarks :)


Best,

Joanna

2018-03-15 8:40 GMT+01:00 >:


One could do that computationally but I would worry about the homology 
it might imply for such variable leaf shapes. You might try it and 
then check to see if, for example, a lobe on one leaf might be 20% of 
the linear distance around the outline but in another it might be 30% 
of the way around. In such a case the lobe on one leaf would 
effectively be treated as homologous to a location between lobes on 
another leaf. If so, does that make biological sense for your study? 
If simple leaves were also included the implied homology of a point 
along its outline to that of one of the lobed leaves might be pretty 
arbitrary. Would be better if one knew something about the development 
of these leaves (which I do not!) and used that knowledge.


An alternative would be to use outline methods to group shapes for the 
purpose of say identification with little implication that groups need 
be biologically meaningful. Sorry to be rather negative but I find 
highly variable leaf shapes difficult to put in a simple standard 
framework. Perhaps others will have better suggestions.




F. James Rohlf, Distinguished Professor, Emeritus. Ecology & Evolution

Research Professor, Anthropology

Stony Brook University

*From:*Tina Klenovšek >

*Sent:* Wednesday, March 14, 2018 12:28 AM
*To:* f.james.rohlf >

*Cc:* morphmet@morphometrics.org 
*Subject:* RE: [MORPHMET] digitizing very variable leaves

Thanks to everyone who answered.

Dear Dr. Rohlf,

I assumed great variability would be a problem.

I was thinking the best way of digitizing would be to draw a curve on 
the outline of each leaf (simple and lobed leaves). Resample curves by 
length with approx. 40 landmarks. Then append curves to landmarks. Two 
landmarks, the leaf tip and base, would be fixed others could be 
defined as semi-landmarks. Is this sensible?


Alternatively, we could analyse simple and lobed leaves separately.

Thank you a lot for your help.

Tina

*From:*f.james.rohlf [mailto:f.james.ro...@stonybrook.edu]
*Sent:* Wednesday, March 14, 2018 3:59 AM
*To:* Tina Klenovšek
*Subject:* Re: [MORPHMET] digitizing very variable leaves

An assumption of the usual GMM methods is that shape variation is 
"small". I think these leaves exceed this quite a bit! Another problem 
is landmarks. How to match leaves with and without lobes?


__

F. James Rohlf, Distinguished Prof. Emeritus

Dept. Anthropology and Ecology & Evolution

Stonybrook University

 Original message 

From: 'Tina Klenovšek' via MORPHMET >


Date: 3/12/18 10:56 AM (GMT-10:00)

To: morphmet@morphometrics.org 

Subject: [MORPHMET] digitizing very variable leaves

Hello everyone,

we would like to digitize tree leaves that are very variable (from 
simple oval to strongly lobed on one tree).


1.)I am wondering if TpsDig can do some kind of automatic digitizing 
like the LeafAnalyser software: 
http://www.plant-image-analysis.org/software/leaf-gp, which evenly 
distributes a defined number of landmarks on the leaf outline...


LeafAnalyser does not seem flexible or precise enough. Or I can’t use 
it properly. Any experience?


2.)Is it possible/sensible to put objects that are so differently 

Re: ***SPAM*** [MORPHMET] Re: Digitizing landmarks on live larvae

2018-03-13 Thread Carmelo Fruciano

Dear Avi,

I guess it's hard to formulate any rule of thumb.

Some analyses might not be defined if the number of variables exceed the 
number of observations. Some other analyses might be defined (there is 
many distance-based analyses nowadays which circumvent that problem).


However, whether a given analysis is defined doesn't mean that the 
inference is necessarily accurate. I guess it depends on what you plan 
to test/measure and the effect size you expect.



Andrea Cardini has some papers that can give you some hint on this, such as:

Cardini & Elton 2007 - Zoomorphology

Cardini et al. 2015 - Zoomorphology

Cardini & Elton 2017 - Hystrix

They should be downloadable from his website 
https://sites.google.com/site/alcardini/home/pubs




Obviously, having an idea of variation on your own data would be better.
I hope this helps.
Carmelo




On 3/12/2018 8:27 PM, Avi Koplovich wrote:

Hi Carmelo,
Thank you for those answers.
One more question please:
I know that the number of specimens should exceed the number of the 
total landmarks (fixed-landmarks + semi-landmarks). Is there a rule of 
thumb of by how much or what ratio between specimens to semi-landmarks 
one should keep?


Thank you,

Avi


On Sunday, March 11, 2018 at 5:15:24 PM UTC+2, Carmelo Fruciano wrote:



Il 6/03/2018 4:44 PM, Avi Koplovich ha scritto:
> Hi Carmelo,
> Thank you for your answer.
> My project tests for the influence of kairomones of a predator
fish on
> the morphology of Salamander larvae during its development. To
do this,
> I take pictures every other week of larvae spawned from six
different
> females and assigned to 3 treatments: No fish, 3 caged fish, 6
caged fish.

Hi Avi,
it sounds like an interesting experiment. I will try to answer to
your
questions but keeping in mind that I'm not very knowledgeable on
salamander development.

>  1. I intend to use landmark 1 (dorsal connection of the tail
fin) as a
>     fixed factor. But I thought I may be able to use the tail tip
>     (landmark 20) and head tip (landmark 48) as fixed landmarks
as well.
>     Do you think it's ok in an ontogeny experiment?

I guess it will depend on how long into ontogeny you will track the
larvae and whether or not that point will "disappear" over ontogeny
and/or slide unreasonably (depends also on your question). You, being
knowledgeable on their biology, are the best judge on that.

> If not, do you think
>     it's ok to slide all semi-landmarks of the tail on landmark
1, and
>     all head semi-landmarks on an eye landmark? Since the eye
isn't part
>     of the head contour, is it ok if I slide one semi-landmark
to the
>     eye and all rest semi-landmarks of the head one to each
other as a
>     closed shape?

The point(s) slid relative to the eye won't be sliding along the
direction tangent to the curve you want to approximate (i.e., the
curvature of the head). A good starting point on the method could be
Gunz & Mitteroecker 2013 - Hystrix

>  2. Is it ok if landmarks 1 and 39 slid relative to each other
as well
>     as 41 and 55, since both describe a closed shape?

It's not particularly desirable (see answer above).

>  3. Another worry I have is that landmark 40 which I used to
create the
>     comb fan for both the tail and the head is too far from both
of them
>     so it doesn't bypass the bending.
>  4. I'm affraid I don't fully understand why landmark 40 can not be
>     treated as a fixed landmark. In the book of Zelditch 2004,
she says
>     that one of the basic differences between fixed-landmark and
>     semi-landmark is the degree of freedom, while fixed has two
because
>     it is docked on both X and Y axes while semi only on one of
them
>     (depending on the nature of the specific fan). Please
correct me if
>     I'm wrong, but what if I use the side line of the larvae
(which is
>     an anatomical/homologous feature) as my X axis and use the Y
>     component of landmark 1 (dorsal connection of the tail fin)
to dock
>     landmark 40 on the Y axis? Is it wrong because of the
dependency of
>     landmark 40 on landmark 1 regarding the Y coordinate?

I think Don has covered these two very well.

>  5. Emma Sherratt told me she straightened the bent tail-body
using TPS
>     software in her paper Sherratt et al. 2017 - Nature ecology &
>     evolution. In the supplementary material of her paper she
wrote:
>     "To correct for dorso-ventral bending in the landmark
configurations
>     (caused by the joint of the tail with the head/body), we
used the
>  

Re: ***SPAM*** [MORPHMET] Re: Digitizing landmarks on live larvae

2018-03-11 Thread Carmelo Fruciano



Il 6/03/2018 4:44 PM, Avi Koplovich ha scritto:

Hi Carmelo,
Thank you for your answer.
My project tests for the influence of kairomones of a predator fish on 
the morphology of Salamander larvae during its development. To do this, 
I take pictures every other week of larvae spawned from six different 
females and assigned to 3 treatments: No fish, 3 caged fish, 6 caged fish.


Hi Avi,
it sounds like an interesting experiment. I will try to answer to your 
questions but keeping in mind that I'm not very knowledgeable on 
salamander development.



 1. I intend to use landmark 1 (dorsal connection of the tail fin) as a
fixed factor. But I thought I may be able to use the tail tip
(landmark 20) and head tip (landmark 48) as fixed landmarks as well.
Do you think it's ok in an ontogeny experiment?


I guess it will depend on how long into ontogeny you will track the 
larvae and whether or not that point will "disappear" over ontogeny 
and/or slide unreasonably (depends also on your question). You, being 
knowledgeable on their biology, are the best judge on that.



If not, do you think
it's ok to slide all semi-landmarks of the tail on landmark 1, and
all head semi-landmarks on an eye landmark? Since the eye isn't part
of the head contour, is it ok if I slide one semi-landmark to the
eye and all rest semi-landmarks of the head one to each other as a
closed shape?


The point(s) slid relative to the eye won't be sliding along the 
direction tangent to the curve you want to approximate (i.e., the 
curvature of the head). A good starting point on the method could be

Gunz & Mitteroecker 2013 - Hystrix


 2. Is it ok if landmarks 1 and 39 slid relative to each other as well
as 41 and 55, since both describe a closed shape?


It's not particularly desirable (see answer above).


 3. Another worry I have is that landmark 40 which I used to create the
comb fan for both the tail and the head is too far from both of them
so it doesn't bypass the bending.
 4. I'm affraid I don't fully understand why landmark 40 can not be
treated as a fixed landmark. In the book of Zelditch 2004, she says
that one of the basic differences between fixed-landmark and
semi-landmark is the degree of freedom, while fixed has two because
it is docked on both X and Y axes while semi only on one of them
(depending on the nature of the specific fan). Please correct me if
I'm wrong, but what if I use the side line of the larvae (which is
an anatomical/homologous feature) as my X axis and use the Y
component of landmark 1 (dorsal connection of the tail fin) to dock
landmark 40 on the Y axis? Is it wrong because of the dependency of
landmark 40 on landmark 1 regarding the Y coordinate?


I think Don has covered these two very well.


 5. Emma Sherratt told me she straightened the bent tail-body using TPS
software in her paper Sherratt et al. 2017 - Nature ecology &
evolution. In the supplementary material of her paper she wrote:
"To correct for dorso-ventral bending in the landmark configurations
(caused by the joint of the tail with the head/body), we used the
‘unbend specimens’ function of tpsUtil v.1.86 (Rohlf 2015). The
landmark configurations for each specimen were transformed using the
quadratic approach, straightening from the eye (1) along the
notochord landmarks (46 to 55) to the tip of the tail (8)."
Jim mentioned this unbending function here before. I read the help
about unbending specimens and thought I can use landmarks 20 (tail
tip), 48 (head tip) and several semi-landmarks I can digitize using
the comb fan (equally spaced) along the side line of the larvae, in
order to create the quadratic curve (while the side line "helper"
semi-landmarks can be later omitted from the dataset - I saw
Fruciano et al. 2016). Does this sound good?
I bet that this can basically solve the problems I mentioned in 3 &
4, since then I can digitized the whole body contour.


That function is great but, as everything, relies on a set of 
assumptions (see also Fruciano 2016 - Development Genes and Evolution 
for a brief discussion). In your case:
- that you can consistently identify those points along an hypothetical 
line (which you would remove after the unbending)

- that your arching is well represented by the chosen function

You are the best judge on whether these assumptions are satisfied in 
your case or not.
I suggested the Valentin et al. (2008 - Journal of Fish Biology) 
approach because it's more flexible (less stringent assumptions, which 
obviously doesn't mean assumption-free) and therefore more generally 
applicable. But, of course, the approach in tpsUtil can be a great 
solution if it's appropriate to your data.


Best,
Carmelo

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Re: Re: [MORPHMET] Digitizing landmarks on live larvae

2018-03-01 Thread Carmelo Fruciano

Dear Avi,
elaborating further also based on Jim's answer, some open 
questions/considerations that you might entertain are:


- if you intend to use sliding semilandmarks (which in general sounds 
like a good idea), how are certain points such as 1,39,41,55 going to be 
slid? (i.e., relative to which other points?) - Notice that in the paper 
you cited the points on the tail are bounded by fixed landmarks. In that 
respect, I wonder if maybe your point 1 could be characterized as a 
fixed homologous point (you define it as "dorsal connection of the tail 
fin")


- I guess that whether the relative position of the eye is useful 
depends on your particular biological question; as Jim said, it might 
actually be interesting; an alternative to using a fixed landmark in the 
eye (at the center of it, I assume) would be to use sliding 
semilandmarks along the contour of the eye. These can be slid relative 
to each other and can give you information on the relative size of the 
eye (which may or may not be of interest for your specific question). 
This seems the solution adopted by Levis et al. (at least looking at 
their figure). Another option with respect to that would also be 
removing the extra semilandmarks after sliding considering them "helper 
points" (see, for instance, fig. 1a in Fruciano et al. 2016 - Ecology 
and Evolution)


- If you can model variation due to arching with a relatively simple 
model, there are methods to account for it, including the one 
implemented in tpsUtil and the one developed by Valentin et al. 2008 - 
Journal of Fish Biology (you can find a discussion of these also in my 
review on measurement error Fruciano 2016 - Development Genes and 
Evolution). Collecting data as accurately as possible in the first place 
is the best idea (and you're doing that), but substantial artifactual 
variation might be still present in your data despite of your best 
efforts (if at all possible, consider also quantifying how similar 
repeated pictures of the same specimens are; you can read about this 
also in the review I mentioned above)


I hope this helps.
Best,
Carmelo


Il 28/02/2018 9:30 PM, Avi Koplovich ha scritto:

Hi James,
Thank you for your fast answer.
I'll continue to mark the landmarks as separated sublets, i.e. head and 
tail.


 1. Is it ok to use landmark 40 (intersection of the side line and the
dorsal connection of the tail fin) as a common mark point to create
a comb fan for both tail and head?
 2. Another question: Is this landmark 40 can be treated as fixed
landmark as it is restricted by both x and y axis?
 3. Can I use landmarks 20 (tail tip) and 48 (head tip) as fixed
landmarks in an ontogenetic experiment?
 4. Last question: Can/Should I use the eye as a fixed landmark for the
head (i.e. can it interfere with interpreting the head contour)?

p.s. I saw your forum message here on updating tpsdig 2.31 and already 
updated it.



Many thanks,

Avi



On Wednesday, February 28, 2018 at 8:51:39 PM UTC+2, f.james.rohlf wrote:

Bending of long slender organisms (or other structures) can be an
important practical problem. Changes due to bending could dominate
the results. Separating sets of landmarks into more rigid sublets
can help as long as the endpoints of the subsets are homologous and
not arbitrary or dependent on the bending of a particular specimen.
The tpsUtil program has an "unending" option if one has a subset of
points that one knows should be in a straight line. That would be
difficult for larvae.

Note: I see you are using ver. 2.30 of tpsDig. Version 2.31 is
current. I do try to keep fixing bugs so It can be useful to stay
current.


F. James Rohlf, Distinguished Professor, Emeritus. Ecology & Evolution
Research Professor, Anthropology
Stony Brook University

-Original Message-
From: Avi Koplovich [mailto:netbird@gmail.com ]
Sent: Tuesday, February 27, 2018 3:09 AM
To: MORPHMET 
Subject: [MORPHMET] Digitizing landmarks on live larvae

Hi,
I've started a new project and came to the point of marking fixed
and semi landmarks.
Not all pictures are satisfying, mostly because of the posture of
the larvae during photographing (sometimes raising it's tail). So in
order to reduce the noise by the animal posture, I thought it would
be helpful to separate head and tail as was done in Levis et. al.
2016, Biol. J. Linn. Soc.
I'm using the landmarks 1, 20 and 48 as fixed landmarks, and all the
rest are semi landmarks. I'm not sure of using 20 and 48 as fixed
landmarks, and I wonder if I can use landmark 40 as fixed landmark
since it is restricted by both x (side line) and y (dorsal
connection of the tail fin). Can/Should I use the eye as a fixed
landmark for the head (i.e. can it interfere with interpreting the
head contour)?

Re: [MORPHMET] p value always identical

2018-01-16 Thread Carmelo Fruciano

Dear Callie,
I am not sure I fully understand your question. Perhaps you could 
provide details as to how your 20 projectile points are transformed into 
data, how the pairwise rotation of two configurations was applied to 
your 20 projectile points, and what is the aim of the test.


Now, let's assume for the sake of argument that you have converted your 
projectile points into data as a set of n 2D landmarks (in the case of 
circle you would have used the same amount of points to form a circle). 
Let's also assume that you have used as starting point for your PROTEST 
two of these configuration of landmarks (i.e., the matrix with n rows 
and 2 columns containing the x,y coordinates of each landmark; one 
matrix for one projectile point, the other for another projectile point).


If the above were true and based on the way the procedure works (in my 
case, I'm referring to the description in Peres-Neto & Jackson 2001 - 
Oecologia), I think a reasonable expectation, for two quite similar 
shapes, would be:
- that after Procrustes superimposition, the x,y coordinates of 
corresponding points/landmarks would be extremely similar, giving a very 
low "Procrustes sum of squares (m12)"
- that randomly exchanging the order of the points in one of the two 
configurations would basically never give you a "Procrustes sum of 
squares (m12)" as small (because, in lay terms, if in one of the two 
landmark configurations you exchange the position of two or more of the 
landmarks, the two shapes will not match as precisely as your original 
configuration)


Blake has given you a potential explanation of why a specific value, 
perhaps my hypothetical scenario (if it applies) can give you a hint on 
why that is always the same.


If the hypothetical scenario above were correct, I would see no special 
issue with the value being always the same (and extremely low). In that 
case, however, there might be an issue with the practical utility of 
performing the test in the first place.


I hope this helps,
Carmelo




Il 16/01/2018 7:51 PM, Callie Diduck ha scritto:


Hi,

I am wondering if any one can help me. I have been running a Procrustes 
Rotation of Two Configurations and PROTEST using the vegan package in R.
The Procrustes seem to be working but I am having an issue with the 
results of the PROTEST and the correlation values.


I am getting identical p values every time I run the script. I have a 
sample size of 20 projectile points and every time I run the statistics 
my p value is
equal to 0.. I ran a test and I compared a circle to one of my 
projectile points and I still got a p value of 0..


Here are the results for the test of the projectile point compared to a 
circle:



Procrustes sum of squares:

1.817e+04

Call:

protest(X = p730, Y = pTest, permutations = 1)

Procrustes Sum of Squares (m12 squared):    0.06296

Correlation in a symmetric Procrustes rotation: 0.968

Significance:  9.999e-05

Permutation: free

Number of permutations: 1


If anyone has any idea of why this could be happening or how to fix it 
that would be greatly appreciated.


Thanks

Callie Diduck

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Re: [MORPHMET] Doubt Scaling photos

2018-01-04 Thread Carmelo Fruciano

Hi Anderson,

I concur with Murat about the usefulness of having actually multiple 
specimens. Analyses on a single specimen, although in principle 
attractive (as one "isolates" error from biological variation), are not 
necessarily informative on a practical level. Also there are two 
problems, one of magnitude (e.g., how large is variation due to 
distance/presentation relative to biological variation), one of 
direction (e.g., if one distance/presentation gets consistently 
digitised differently from the other, that is, you have non-random 
error/bias). You can find discussions of these in my recent review which 
Murat very kindly suggested.



I would add that, in addition to the digitization process, differences 
might have been caused by factors. However, another thing that I noticed 
in your TPS file is that you have first all the repetitions at one 
distance, then all the others. So I assume you digitized them in that 
order. This suggests that, as already pointed out by Murat, the 
differences might be due to "learning" or changes over time in the way 
you digitize.



Most likely, the final error will come from a combination of various 
sources, as it's generally the case.



In general, I would suggest you to run a larger preliminary analysis with:

- multiple biological specimens

- multiple distances

- multiple digitizations

- digitizing in random order across repetitions (there is a very useful 
function for this in tpsUtil by F.J. Rohlf)


- using multiple statistical tools to gauge how large is the error 
relative to biological variation and if there are non-random patterns



I hope this helps,

Carmelo




Il 2/01/2018 7:28 PM, Murat Maga ha scritto:


Hi Anderson,

I don’t think PCA is the tool you want to use in this context. 
Procrustes anova already tells you that your two magnification levels 
are done differently. Since your question is ‘can I combine data from 
different magnification level in the same analysis?’, the answer to 
that in your current study design (single sample measured five times 
at two different scales) is a very qualified no.


But, what is more relevant, (or what I would have liked to know) the 
magnitude of this error in context of actual biological variation.


For that, you have to have a study design where you have a few samples 
of different sizes measured at different magnification scales a couple 
times (not just measuring the same object repeatedly in different 
magnifications), or something along those lines.


There is a really a lot of literature on this.  But you need to use a 
statistics based framework, not EDA tools like PCA to answer this.


M

*From:* Anderson Feijo [mailto:andefe...@gmail.com]
*Sent:* Monday, January 1, 2018 11:02 PM
*To:* Murat Maga 
*Cc:* MORPHMET 
*Subject:* Re: [MORPHMET] Doubt Scaling photos

Dear Murat,

Thank you very much for your email and time for explore my dataset. To 
perform this simple experiment, given the aim was to explore the 
magnification issue, I chose only three landmarks (as you could see in 
the tps file) easily to replicate. The reason I am trying to combine 
two magnification is that I will work with groups with different 
sizes; for example, species with 10 cm and others with 3 cm of total 
length of skull. Place the camera at a good distance to avoid parallax 
for the large group will lead a low resolution images of the small 
groups. Thus, my initial idea was to have two standardized distances 
and combine later after accounting the scale effects.


In my short experiment, what intrigues me is the clear groups in PCA 
(and other exploratory analyses) based on the two magnifications (see 
below). At the beginning, I was expecting a great overlap between the 
two distances and minimum differences due to landmarks-placement error 
as seen within each of the group.


Best,

Anderson

Inline image 1

On Sat, Dec 30, 2017 at 3:57 PM, Murat Maga > wrote:


Dear Anderson,

It has nothing to do with the scale of your data (or least not
directly).

As you can see, you actually performed those two digitization
attempts differently. It is maybe 1-2 pixels off, but in a very
consistent way (greens are from one scale, red is the other scale,
and cross is the consensus shape). This type of systematic error
commonly occur in digitization process, as one learns better or
alters the way landmarks are digitized/defined along the process.
In your case, perhaps higher resolution image gave a better
definition (imaging sense) of landmarks, so you captured them very
slightly differently than low-res image (but in a very consistent
way).

If you are concerned, the first step perhaps is to do the same
thing (i.e. digitization of same sample with different
magnifications several times) with several real specimens and get
a sense of the magnitude of this error in context of the
 

[MORPHMET] New publication - measurement error

2017-10-08 Thread Carmelo Fruciano

Dear all,

perhaps this new publication of mine (on measurement error) could be of 
interest to some people in the list.


http://onlinelibrary.wiley.com/doi/10.1002/ece3.3256/full

Best,

Carmelo


==
Carmelo Fruciano
School of Earth, Environmental & Biological Sciences
Queensland University of Technology
+ 61 7 3138 84467

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Re: [MORPHMET] Question on TPS and lack of scale

2017-09-04 Thread Carmelo Fruciano

Dear Ely,

the coordinates will be expressed as their pixel position. Clearly, in 
many/most cases (e.g., different magnification in different pictures) 
the size information you can extract from these configurations of 
landmarks is not usable unless you manage to get that information in 
some other way. Shape will be fine.


Best,

Carmelo


Il 4/09/2017 6:49 PM, Ely Raz ha scritto:


Dear All,

I will have a TPS file without scales. How does it effects the 
analysis? Any papers or data that I can read or examine?


Thanks

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Re: [MORPHMET] Save aligned in TPSRelW

2017-06-22 Thread Carmelo Fruciano

Dear Pere,

there are various workarounds to that.  For instance, one can convert 
the original tps file to an nts file and then copy the line with the 
labels from the original nts to the tps with aligned specimens. Another 
option, which is useful when one has the names in the file names and not 
in IDs is to use the function "list images in tps files" in tpsUtil. 
This actually saves a lot of time as one doesn't have to input the ids 
one by one.


Although this doesn't answer exactly your question, it should be good 
enough in many (most) situations.


Best,

Carmelo


Il 22/06/2017 6:07 PM, Pere Ibáñez ha scritto:

Hello All,

I am using TPSRelW to slide semilandmarks. Once I have the consensus, 
I use Save aligned to export the aligned coordinates (including slid 
semilandmarks) as a tps file, that I want to import into MorphoJ.


The problem is that the file that is exported has the IDs of the 
specimens empty, with no information. And MorphoJ doesn't import it 
without that information, so I have to type it one by one on the tps 
file. Does anyone know how to export that tps file from TPSRelW 
without losing the ID?


Thanks!
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Re: [MORPHMET] Re: Interpreting PCA results

2017-05-16 Thread Carmelo Fruciano

Dear Morphmet list,

first, thank you all for the very interesting and stimulating posts.

In my humble opinion, not being PCA a "predictive" tool, it can be 
easily misused as such. Personally, I most frequently use PCA to have a 
quick look at what my data looks like. In other words, to look at 
obvious patterns in multivariate data, which would be otherwise very 
hard to visualize. I often don't feel the need to mechanically (to echo 
Dr. Rohlf) describe what shape change each PC axis (especially after the 
first) explains. In most cases, there are other tools for hypothesis 
testing, modeling and so on. But the immediate first look that I get 
from simply plotting ordinations is very hard to obtain in other ways. 
Trying to use PCA as a predictive tool, in my opinion, can equal to 
"forcing" it for a use that it is not perfectly fit for. It does work in 
some cases, but if that is reasonable or not is more of a case-by-case 
decision. This point is hardly original as most, if not all, the people 
who answered this far have raised it, but phrased it differently.


I also found the question by Dr. MacLeod very stimulating. I imagine 
that PCA, in its use as a dimensionality reduction tool (as 
controversial as it might be), and in conjunction with other techniques, 
can be used to produce realistic morphospaces. In other words, by 
"separating the wheat from the chaff" first and then modeling shape in 
this subspace (for instance, explicitly as a vector of shape in a 
certain direction) we can perhaps get an outcome that is realistic, with 
reduced amounts of variation in directions that are not of interest 
(perhaps because we consider them noise). The use of PCA in this context 
might not be strictly necessary, but would probably still useful when it 
comes to thinking about and visualizing the morphospace.


To be clear, I'm not advocating a generalized use of dimensionality 
reduction, just its potential in certain contexts.


Best wishes,

Carmelo




On 16/05/2017 10:55 PM, dsbriss_dmd wrote:

Good morning all,

I would like to thank everyone so far for generously taking the time 
to reply to my questions:  I didn't think I would generated such an 
interesting discussion!  As an amateur morphometrician I am trying to 
keep up and have started reading some of the literature you all have 
cited.


From what I understand so far, the PCA is a statistical result that 
describes the variance in a shape, and the warp visualization that is 
extrapolated from the PCs is one method to describe the statistical 
variance.  I think this is what I was getting at by saying that the 
PCA didn't have a "real" biological basis (sorry for my inaccurate 
language).   James you identified my main problem, in that how does 
one move from this virtuality into the real world?  Or more to the 
point, how does the reader, who is not necessarily well versed in 
geometric morphometrics, interpret  PCA results in real-world shape 
spaces, perhaps without this visualization?


The replies from Profs. MacLeod and Rohlf also get a bit at what I was 
after, in that how does one decide which axes in PCA are of interest 
in the first place, or indeed which landmarks are of interest, and 
avoid the trap of mechanically displaying a warp (of whatever extreme) 
simply to provide a visualization?  That question about the way we use 
these spaces is also important to know, as one of the questions I 
usually get from my residents or faculty colleagues is what clinical 
application the PCA has; I usually find that I have to explain that it 
doesn't have a clinical significance or application, as by itself it 
is not a description of a real clinical situation.


What they seem to want me to say is, can the PCs derived from GPA be 
used as a predictive tool to describe how an individual shape will 
change over time.  My usual answer is no, it cannot be used that way. 
 I think that the warped PCA, whatever criteria are selected, might 
help to visually explain how an individual differs from the Procrustes 
shape, but in the average orthodontic reader I am not sure it is 
interpreted this way.  This may be a quirk of our specialty, since we 
have been using landmark-based linear and angular analyses as growth 
predictive tools since the 1940's.


I don't want to say that we are wrong to do this, but the issue comes 
in trying to apply those long-used clinical tools to geometric 
morphometrics, and I don't think they mesh very well.  And as we get 
closer to 3 dimensional analysis those older tools won't be able to 
apply anymore.  From a standard cephalometric approach I might be able 
to claim that cranial base angle (Nasion-Sella-Basion) has some 
correlation with mandibular prognathism, but I am not sure that this 
is true from a geometric morphometric perspective, as I can't (yet) 
answer what the covariance is between the cranial base and the 
mandible, for example.


Anyway thank you all again, this is a very interesting thread and I 

Re: [MORPHMET] Interpreting PCA results

2017-05-15 Thread Carmelo Fruciano

Dear Mahediran,

to my understanding from David's phrasing, it is just a way to visualize 
shape variation along a given PC axis (as the value at 0 is the mean). 
One could use some other criterion (for instance the maximum and minimum 
scores along that given PC).


But, of course, all the other considerations of whether or not it makes 
sense to interpret (or at least explore) the patterns predicted along a 
given PC axis still apply.


Best,

Carmelo


Il 15/05/2017 4:30 PM, mahendiran mylswamy ha scritto:

Dear all,
I read interesting comments and the attached manuscript as well.
I find David question us interesting.
If any one could answer David question in a simple way?
I am quoting his question below?.
"What I do not quite understand is what exactly is the purpose of 
applying standard deviation(s) to the PCA and then warping the 
Procrustes average shape to these standard deviations? "



On 15 May 2017 6:08 a.m., "F. James Rohlf" 
> 
wrote:


I agree with these comments but would like to add another point. I
prefer to think that the purpose of the PCA is to produce a
low-dimension space that captures as much of the overall variation
(in a least-squares sense) as possible. Within that space there is
no need to limit the visualizations to the extremes of each axis –
one can investigate any direction within that space if there is a
pattern in the data that suggests an interesting direction. The
directions of the axes are mathematical constructs and not bases
on any biological principles. Perhaps one sees some clusters in
the PCA ordination but the variation within or between clusters
need not be parallel to one of the PC axes. One can then look in
other directions. That is why the tpsRelw program allows one to
visualize any point in the ordination space – not just parallel to
the axes. That means for publication one has to decide which
directions are of interest – not just mechanically display the
extremes of the axes.

--

F. James Rohlf *New email: f.james.ro...@stonybrook.edu
*

Distinguished Professor, Emeritus. Dept. of Ecol. & Evol.

& Research Professor. Dept. of Anthropology

Stony Brook University 11794-4364

WWW: http://life.bio.sunysb.edu/morph/rohlf


PPlease consider the environment before printing this email

*From:* K. James Soda [mailto:k.jamess...@gmail.com
]
*Sent:* Sunday, May 14, 2017 7:28 PM
*To:* dsbriss_dmd >
*Cc:* MORPHMET >
*Subject:* Re: [MORPHMET] Interpreting PCA results

Dear David,

Great question!  I disagree with the statement that the samples'
variance in shape space is not biologically real or, perhaps more
accurately, is less real than the variance in any other space.  As
far as I see it, the basic strategy in any biostatistical study,
be it GM or otherwise, is that a researcher represents a real
biological population as an abstract statistical population.  They
then use this abstract statistical population as a proxy for the
real one so that inferences in the statistical space have
implications for the real world.

For example, a PCA finds a direction in the statistical space in
which the statistical population tends to be spread out.  This is
interesting to the researcher because this direction has a
correspondence to certain real world variables.  As a result, the
PCA tells the researcher in what ways the real population tends to
vary.  The key point, though, is that the researcher transitioned
from the statistical space to the real world.

Moving from shape space to the real world is no different in
principle.  We have a real population of specimens, whose shape
are of interest to us, and we represent them using vectors of
shape variables.  The vectors are abstractions; it is not as if we
can hold a vector in our hands. However, this is irrelevant
because they are just proxies, no less real than any other
quantitative representation.  What matters is if we can tie them
back to the real world.  This is why morphometricians implement a
visualization step. In a PCA, the PCs describe how our proxies
vary, and we visualize in order to see how this variation appears
in the real world.  It is infeasible to visualize every point
along this axis, so we instead visualize a handful.  Since the
core goal in PCA (at least in this context) is to describe
variance, we generally describe the locations where a
visualization occurs in units of standard deviations from the
mean.  We could use absolute distances along an 

Re: [MORPHMET] curve analysis

2017-04-25 Thread Carmelo Fruciano

Ioannis Maniakas <biojohn...@gmail.com> ha scritto:

Hello everyone. As I am new in the field of the geometric  
morphometrics, I am expressing my naive problem..
I am trying to analyze differences in the shape of two simple  
separate curves. These describe the radii of circles fitting to the  
condylar margins on the proximal and distal articular surfaces of  
the medial astragalar side respectively.
I think I have followed the standard procedure. The recorded curves  
were resampled (always from a common homologous starting and ending  
position), granting the same number of evenly spaced 50 points (“by  
length” option in tpsDig) across all specimens.


I would double-check that corresponding points across different  
specimens sample the same structure.


Afterwards, the operation of converting into landmarks was conducted  
with the employment of the tpsUtil program resulting in 50 landmark  
configurations.
So, my question is this: can I import their coordinates into Morphoj  
or even Past and ran  the whole analysis there, including the  
superimposition? Or do I have to treat these data in an other way?


No. If these are, in fact, semilandmarks, these should be treated  
accordingly (sliding).


I have tried to make a slider file for both curves (2 landmarks at  
the two ends of the curves and 48 sliding landmarks between). As I  
load these nts files with the tps file with my 50 lanmarks in  
tpsrelw and perform the analysis there, the consensus and the rest  
results are wrong. More specifically, the position of landmarks has  
changed dramatically, as some of them have overslided and there are  
not placed equidistantly.


I would check different criteria for sliding (menu Options of tpsRelW).
Also, there are various discussions of criteria and relative  
advantages you might want to consult, such as

Perez et al 2006 - Journal of Anatomy
Gunz & Mitteroecker 2013 - Hystrix
To memory, the latter explicitly discusses a case which sounds similar  
to yours.



Also, it  seems that right and left specimens are not getting aligned at all.


I guess I would align them separately (unless you want to reflect and  
relabel one of the two sides prior to superimposition, which I imagine  
you'd have to do "manually"/scripting).


This was not the case, when I simply treated them as typical  
landmarks in morphoj..


That is because the Procrustes fit in MorphoJ includes reflection. You  
can find a description of this in the MorphoJ user guide.


I hope this helps,
Carmelo


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Australia

Honorary Fellow - University of Catania - Catania, Italy
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Re: [MORPHMET] MorphoJ Text File Formatting

2017-04-25 Thread Carmelo Fruciano


Alicja Witwicka <a.s.witwi...@gmail.com> ha scritto:


Hello everyone,
I am a complete beginner in geometric morphometrics and I have met  
one problem. Namely, when I try to upload the .tps file created in  
tpsUTIL to MorphoJ software I receive the following communicate:


"Problem with the text file: Line 1 contains less than two entries:
LM=7
Note: A frequent reason for this problem is that the file contains  
delimiters other than commas or tab stops.

Errors occurred in the reading process.
The new dataset could not be created."

I have tried to change the data manually but it does not work.  
Anyway, I have too many specimens to manage that in such a way. Do  
you possibly know where I can find the source of that problem?


Hi Alicja,
Did you select the appropriate format in the import window?
To my understanding, you would get that error if you were importing a  
file in TPS format but you had left the default "text" selected,  
instead of switching to TPS under "File Types" on the "Create new  
dataset" menu.

I hope this helps.
Best,
Carmelo


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Honorary Fellow - University of Catania - Catania, Italy
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Re: [MORPHMET] Merge MorphoJ files

2017-04-20 Thread Carmelo Fruciano

Aixa del Olmo <aixa@gmail.com> ha scritto:


Hi everyone,

I've received a MorphoJ file from one of my collaborators, and I am
supposed to put together her analysis and mine's. Does anyone know how to
merge both morphoJ files? The other option is to append the two tps files
with tpsUtil, but I will have to re-do all the analysis in morphoJ.
Thank you very much,


Hi Aixa,
I don't know of any automated solution and I'm by no means expert in  
these MorphoJ details (maybe Dr. Klingenberg will chime in).
However, I notice that the .morphoj files are nicely formatted XML  
files (with indentation and all).
I tried to combine two sets of analyses (each containing different  
datasets) by putting together different morphosets (opening and  
closing tag ) and it seems to work (all nested within a  
single morphojproject).
Please, keep in mind this is undocumented and might not always work.  
But I guess it's easy enough to give it a try using an advanced text  
editor (such as Notepad++).

I hope this helps,
Carmelo



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Honorary Fellow - University of Catania - Catania, Italy
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Re: [MORPHMET] Deformation Grids

2017-02-12 Thread Carmelo Fruciano

geoffrey marselli <geoffrey11...@gmail.com> ha scritto:


HI everyone,
I am a french student of University of Paul Sabatier, and for my  
internship of master 1, I would like to produce deformations grids  
on MorphoJ.


So I have specimen of various sites, and I would like to create  
grids (with canonical variable analyse) for every sites for then  
compare them.
I know how to create a grid of the CVA with all my specimens,  but  
not how to create grids by classifiers.

Thanks
Geoffrey

PS: Scuse me for my english


Hi Geoffrey,
to my understanding and knowledge, the closest to what you describe  
are the deformation grids that you obtain using the "Discriminant  
Function..." module, which display the deformation between two group  
means (further info in MorphoJ user guide).

Cheers,
Carmelo


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Australia

Honorary Fellow - University of Catania - Catania, Italy
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Re: brief comment on non-significance Re: [MORPHMET] procD.allometry with group inclusion

2016-12-12 Thread Carmelo Fruciano
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tel. 0039 059 2058472

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Re: [MORPHMET] geiger rescale error

2016-12-06 Thread Carmelo Fruciano

Hi Andrea,
I have run the code you posted without problems.
In this moment, I'm using R 3.3.2 x64 on a Windows machine.
The geiger version I tried this on is geiger_2.0.6.
You might wanna try also posting the question on the list R-sig-phylo  
as a lot of people developing R packages for phylogenetic comparative  
approaches are subscribers there (and that's why I'm answering to you  
publicly).

Best,
Carmelo

andrea cardini <alcard...@gmail.com> ha scritto:


Dear All,

I've just tried the rescale function in geiger on my data and got an  
error message. As I have no experience with it, I tried the first  
example for this function in the help: same error message (see below).


Has anyone had similar issues? Probably I made some silly mistake.

Thanks in advance for your feedback.

Cheers


Andrea


geo <- get(data(geospiza))
ltrns <- rescale(geo$phy, "lambda")
plot(ltrns(0))
title("lambda: 0.0")

Error message:

Error in rescale(as.numeric(x, range = range, domain = domain, ...)) :
  (list) object cannot be coerced to type 'double'


--

Dr. Andrea Cardini
Researcher, Dipartimento di Scienze Chimiche e Geologiche,  
Università di Modena e Reggio Emilia, Via Campi, 103 - 41125 Modena  
- Italy

tel. 0039 059 2058472

Adjunct Associate Professor, School of Anatomy, Physiology and Human  
Biology, The University of Western Australia, 35 Stirling Highway,  
Crawley WA 6009, Australia


E-mail address: alcard...@gmail.com, andrea.card...@unimore.it
WEBPAGE: https://sites.google.com/site/alcardini/home/main

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ESTIMATE YOUR GLOBAL FOOTPRINT:  
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Re: [MORPHMET] Re: the problem with CVA... or is it?

2016-11-28 Thread Carmelo Fruciano

Christy Hipsley <chips...@museum.vic.gov.au> ha scritto:


Sorry I should have been more clear - the CVA was done using individual
shapes, so n=161, and the bgPCA was on species means (the basic unit of my
study), so n=92. I did the CVA on the individuals so as not to have more
"groups" than variables and avoid false separation. I've seen your bat
paper and indeed thought of doing something similar. I just liked the CVA
because it showed very well the environmental gradient along which the
different cranial shapes fall.


One (e.g., a reviewer) might wonder if the pattern observed in CVA but  
not in bwgPCA is due to CVA and not to the pattern being real. After  
all, if the environmental gradient is in some way important, that can  
be analysed/plotted directly (I really don't know enough to gauge if  
this is feasible or not in your particular case, just saying)


Best,
Carmelo



P.S. Here, the issue is not demonizing CVA but, rather, understanding  
what is it for and using it for the right purposes.



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e-mail c.fruci...@unict.it
http://www.fruciano.it/research/





On Tuesday, November 29, 2016 at 10:04:02 AM UTC+11, Christy Hipsley wrote:


Dear Morphmet-ers,

I'm seeking advice on methods for visualizing shape features that
distinguish multiple groups using GM. I know CVA has fallen out of favor
for a number of reasons discussed here - e.g., more variables than groups,
nonisotropic variation:

Mitteroecker, P., and Bookstein, F. 2011. Linear discrimination,
ordination, and the visualization of selection gradients in modern
morphometrics. Evol. Biol. 38:100–114.
Klingenberg, C. P., and Monteiro, L. R. 2005. Distances and directions in
multidimensional shape spaces: Implications for morphometric applications.
Syst. Biol. 54:678–688.

Although given these limitations, is it really expected to give completely
false results regarding the visualization of shape changes? In my study
sytem, I show that ecological groups have statistically different cranial
shapes, using both Procrustes ANOVA and PGLS. Now I simply want to
visualize what the main features are that distinguish them, preferably
using warps or wireframes, so that those changes must be directly
relateable to the original landmark coordinates. I did that using
individual specimens instead of species means, so I have 161 individuals vs
144 variables (48 landmarks*3D). I also did a between-group PCA on the
species means which shows the same pattern, so is it technically "wrong" to
show both?

Thanks for any feedback on this issue, and I would appreciate to hear any
alternative methods that people might use. I use MorphoJ and Geomorph for
analyses.

Best,
Christy



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Re: [MORPHMET] the problem with CVA... or is it?

2016-11-28 Thread Carmelo Fruciano

Dear Christy,
I'm not sure I understood the part on doing it "using specimens and  
not species".


As you know, Mitteroecker & Bookstein (2011) suggest between-group  
principal components. Personally, I have used this technique multiple  
times (e.g., Fruciano et al 2014 - Biological Journal of the Linnean  
Society; Fruciano et al 2016 - Ecology and Evolution), and I'm very  
happy with it. I see no special reason, in normal situations, to show  
both between-group PCA and CVA ordinations as the ordinations of the  
latter show overly "optimistic" separation of groups.


Having said that, species/group means are means so if that's what  
you're visualizing shape change as differences between group means it  
doesn't really matter (notice, for instance, how MorphoJ produces,  
under the module "Discriminant Analysis" a plot of differences between  
group means).


Perhaps, if the number of your groups is small enough you want to  
consider a visualization like the one we did for bats (Schmieder et al  
2015 - Plos One; Fig. 3) where we show both shape change associated  
with between-group PC1 and each species mean compared to the grand  
mean. Pairwise comparisons of species/group means are another  
alternative, depending on the number of groups and, most importantly,  
the point you want to make.


I hope this helps,
Carmelo

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Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
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Christy Hipsley <chips...@museum.vic.gov.au> ha scritto:


Dear Morphmet-ers,

I'm seeking advice on methods for visualizing shape features that
distinguish multiple groups using GM. I know CVA has fallen out of favor
for a number of reasons discussed here - e.g., more variables than groups,
nonisotropic variation:

Mitteroecker, P., and Bookstein, F. 2011. Linear discrimination,
ordination, and the visualization of selection gradients in modern
morphometrics. Evol. Biol. 38:100–114.
Klingenberg, C. P., and Monteiro, L. R. 2005. Distances and directions in
multidimensional shape spaces: Implications for morphometric applications.
Syst. Biol. 54:678–688.

Although given these limitations, is it really expected to give completely
false results regarding the visualization of shape changes? In my study
sytem, I show that ecological groups have statistically different cranial
shapes, using both Procrustes ANOVA and PGLS. Now I simply want to
visualize what the main features are that distinguish them, preferably
using warps or wireframes, so that those changes must be directly
relateable to the original landmark coordinates. I did that using
individual specimens instead of species means, so I have 161 individuals vs
144 variables (48 landmarks*3D). I also did a between-group PCA on the
species means which shows the same pattern, so is it technically "wrong" to
show both?

Thanks for any feedback on this issue, and I would appreciate to hear any
alternative methods that people might use. I use MorphoJ and Geomorph for
analyses.

Best,
Christy

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[MORPHMET] New publications

2016-10-31 Thread Carmelo Fruciano

Dear Colleagues,
I'd like to notify you about a few recent publications of mine with  
morphometric content.

Thanks for your attention and best wishes,
Carmelo Fruciano



Fruciano, C.*, Franchini, P.*, Kovacova, V., Elmer, K., Henning, F.,  
Meyer, A. 2016. Genetic linkage of adaptive traits in sympatrically  
speciating Midas cichlid fish. Nature Communications 7, 12736


Fruciano, C. 2016. Measurement error in geometric morphometrics.  
Development Genes and Evolution 226(3), 139-158.


Fruciano, C., Franchini, P., Raffini, F., Fan, S., Meyer, A. 2016. Are  
sympatrically speciating Midas cichlid fish special? Patterns of  
morphological and genetic variation in the closely related species  
Archocentrus centrarchus. Ecology and Evolution 6(12),4102-4114


Jones, J.C., Fruciano, C., Keller, A., Schartl, M., Meyer, A. 2016.  
The male intromittent organ: key to species diversification in  
live-bearing fishes? Ecology and Evolution 6, 7207-7220.


Franchini, P., Colangelo, P., Meyer, A., Fruciano, C.  2016.  
Morphometric variation in parapatric Robertsonian races of the house  
mouse Mus muscuslus domesticus. Ecology and Evolution 6(5), 1353-1362.





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Australia

Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

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Re: [MORPHMET] Interpreting PC scores graph in MorphoJ when the first two PC's are difference due to operator input

2016-10-09 Thread Carmelo Fruciano

Dear Helmi,
I won't answer you in detail on your specific case as I didn't fully  
understand the problem/design.


Ideally, if you have at least a subset of the same bones being  
digitized by all the users/operators, you can check for your  
hypothesis 1.


In some cases it might be possible to "remove" measurement error from  
your data using the method presented in


Valentin AE, Penin X, Chanut JP, Sévigny JM, Rohlf FJ (2008) Arching
effect on fish body shape in geometric morphometric studies. Journal of Fish
Biology 73:623–638. doi:10./j.1095-8649.2008.01961.x

That method and other approaches/issues are also discussed in my  
recent review on the topic of measurement error


Fruciano C (2016) Measurement error in geometric morphometrics.  
Development Genes and Evolution, 226(3):139–158. doi:  
10.1007/s00427-016-0537-4.


which might be useful to you to understand what's possible to do in  
your specific case.


I hope this helps,
Carmelo





Helmi Hadi <helmih...@gmail.com> ha scritto:


Dear Morphometricians,

I have a weird problem and I was hoping someone could help me on this.

I have the same CT bone (n=400) with 14 landmarks (2 Single point and 12
sliding) larndmarked in IDAV Landmark by three different individuals
following a figure key table. Each individual landmarked 100+ different
bones. The figure key table has the shape of the bone, with the landmark
locations and the order of landmarking. All users were briefed by a single
person (user1) on how to extract the bone and landmark. All three
individuals were present throughout the entire procedure but the bone
segmentation and landmarking process was conducted individually.

When I combine all the data, I noticed that PC1 and PC2 graph has two
clusters. The effect is about 55% (as detailed in the eigenvalues below)
After further checking the classifiers in MorphoJ, the source of the
clustering is one person (user1) landmarked it is slightly differently
compared to the other two. I have checked the outliers tab and no glaring
outliers exists. As the sample size is big, the curve seem to be quite
normal.

Eigenvalues  % Variance Cumulative %
  1. 0.01603351  55.674   55.674
  2. 0.00496222  17.230   72.904
  3. 0.00224594   7.799   80.703
  4. 0.00121085   4.204   84.907
  5. 0.00076858   2.669   87.576
...

How to interpret the results for this kind of data? Things which come to my
mind are:

1. Maybe the bones for user1 are different compared to the other two users.
Or
2. User1 thinks the landmark location slightly different compared to others.
Or
3. User2 and 3 could not locate the landmark locations of user1.
Or
4. The landmarks selected are unreliable.

Ideally I would need few other people relandmark the entire set, but it is
not possible to do it now. Can anyone help shed some light on what is the
probable cause? Thank you.


Kind regards,

Helmi Hadi, PhD
 School of Health Sciences, Universiti Sains Malaysia,
16150 Kubang Kerian, Kelantan, MALAYSIA


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Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

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Re: [MORPHMET] Form Space?

2016-04-03 Thread Carmelo Fruciano

Ariadne Schulz <ariadne.sch...@gmail.com> ha scritto:


Hello All,

I have another rather silly question that I'm hoping either has a very
simple answer or will set off another wave of debate. I'm still on about my
3D semilandmarks and now I want to plot them in form space in R. I have my
original landmarks and my GPA coordinates and centroid size from gpagen
with a sliding function, and so forth so the new version of plotAllometry
should work, but I really want to plot in form space. It seems to me I'm
just missing something really easy. Is there a way to do this?


Dear Ari,
if you are referring to plots of principal components/relative warps  
in "size-shape space", as defined by Mitteroecker et al 2004 (Journal  
of Human Evolution), it is basically a PCA on Procrustes coordinates +  
log centroid size. Reading of the original paper is also useful to  
understand the idea and its application.


I don't know if this approach is implemented "out of the box" in some  
R package but, given its simplicity, it's easily obtained referring to  
the original publication by using even basic R function or other  
general-purpose statistical software.


You can see an example of these plots in one of my own papers  
(Fruciano et al 2012 - Environmental Biology of Fishes) and, really,  
in many others, where it is used to produce exploratory plots.


I hope this helps.
Best,
Carmelo

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Australia

Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

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Re: [MORPHMET] Doubts about Error Measurement

2016-03-19 Thread Carmelo Fruciano

Hi Liu,
I'm not sure I understand your question.
Those are the percentages of the total sum of squares due to each of  
those terms and, yes, as you can see from the numbers, they all add up  
to 100%.


Of course, you can quantify only what you measure, and you cannot  
exclude that there are other sources of error than the ones you tested  
(I say this because of your wording "total error").


I hope this helps,
Best,
Carmelo



Liu Idárraga <liuidarr...@gmail.com> ha scritto:


And respect to the total error, the sum of the % SSimage + % SSdig?

Liu

2016-03-15 21:38 GMT-03:00 Carmelo Fruciano <c.fruci...@unict.it>:


Liu Idárraga <liuidarr...@gmail.com> ha scritto:


Appreciated colleagues.

I have some doubts about the correct calculation of error in my data. I
had
understood that the error corresponde to the proportion that represent the
SS of each effect (image / digitalization) in the SStotal; but I found in
the classical paper of Bayley & Byrnes 1990. Syst. Zool. 39(2):126 that
the
way to calculate the percent of the measurement error is:

% ME = 100%  s2 within / (s2 within - s2 among)

s2 within = MS within
but
s2 among = (MS among -MS within)/# replicates

​I have the followed results for 71 ind in 2D, and 44 coord (66 - 4 -
18 semi landmarks)


Procrustes ANOVA para la forma: con g.l. corregidos
Efecto SS SS (%) MS df F p (param.)
Individuo0,26857296 92,84 8,59709E-05 3124 25,97 <.0001
Imagen 0,01048868 3,63 3,31082E-06 3168 2,05 <.0001
Digitalización 0,01021206 3,53 1,61175E-06 6336
Total 0,28927370 100,00

​My questions are:
​1) Is correct to say that 3,63 and 3,53 are the errors of image and
digitalization?
2)  Is the total error equal to 3,63 + 3,53 or I should calculate it with
the equations of Bayley & Byrnes 1990?

In advance, thanks a lot for the help.

Liu



Dear Liu,
Perhaps the best way to report this would be to say that 3.63% of the
total sum of squares is accounted for by/due to a certain term
(digitization, preparation)?
Best,
Carmelo



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Australia
Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

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*Liu Idárraga*
Estudiante doctoral
Facultad de Ciencias Naturales y Museo
Universidad de La Plata - Argentina

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Australia

Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

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Re: [MORPHMET] Doubts about Error Measurement

2016-03-15 Thread Carmelo Fruciano

Liu Idárraga <liuidarr...@gmail.com> ha scritto:


Appreciated colleagues.
I have some doubts about the correct calculation of error in my data. I had
understood that the error corresponde to the proportion that represent the
SS of each effect (image / digitalization) in the SStotal; but I found in
the classical paper of Bayley & Byrnes 1990. Syst. Zool. 39(2):126 that the
way to calculate the percent of the measurement error is:

% ME = 100%  s2 within / (s2 within - s2 among)

s2 within = MS within
but
s2 among = (MS among -MS within)/# replicates

​I have the followed results for 71 ind in 2D, and 44 coord (66 - 4 -
18 semi landmarks)


Procrustes ANOVA para la forma: con g.l. corregidos
Efecto SS SS (%) MS df F p (param.)
Individuo0,26857296 92,84 8,59709E-05 3124 25,97 <.0001
Imagen 0,01048868 3,63 3,31082E-06 3168 2,05 <.0001
Digitalización 0,01021206 3,53 1,61175E-06 6336
Total 0,28927370 100,00

​My questions are:
​1) Is correct to say that 3,63 and 3,53 are the errors of image and
digitalization?
2)  Is the total error equal to 3,63 + 3,53 or I should calculate it with
the equations of Bayley & Byrnes 1990?

In advance, thanks a lot for the help.

Liu


Dear Liu,
Perhaps the best way to report this would be to say that 3.63% of the  
total sum of squares is accounted for by/due to a certain term  
(digitization, preparation)?

Best,
Carmelo



--
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Postdoctoral Fellow - Queensland University of Technology - Brisbane,  
Australia

Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

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Re: [MORPHMET] Using photographs from distinct sources to GM analyses

2016-03-13 Thread Carmelo Fruciano

Dear Pablo,
I'm not sure I got all the nuances of your problem.
Just some random thoughts:

- if you cannot measure how similar/consistent are different methods  
on the same skulls (or at least a subset) it becomes very hard to say  
with certainty if combining different sources of data does or does not  
affect the analysis


- perhaps one way to have an idea is to get a homogeneous subset  
(relative to what you are studying) with both methods and see if the  
different observations cluster by method


- often times, centroid size tends to be more consistent across  
repetitions than shape information. This, of course, doesn't say if  
you will have a bias between dataset but personally I would be more  
worried about shape


- if you have a scale bar in your pictures, I would imagine that the  
computation of size will not be affected much while shape might be  
much more affected by stuff like different levels/types of distortion  
introduced by using different equipment (cameras). If you don't have a  
scale bar, well, that's a can of worms unless you have some other  
measurement that you can use as scale (that's perhaps what you're  
alluding to when saying that you will "compute centroid size from  
traditional measurements")


It is a quite vast topic. I have touched upon this and other issues in  
a review on measurement error in morphometrics which should be online  
soon(ish). I will post it here when it will be available.


Best,
Carmelo




Pablo Fisichella <fisichellapa...@gmail.com> ha scritto:


Dear Morphometricians

I am new in geometric morphometrics. I have a question perhaps quite simple
with regards to 2D GM. I am comparing the size/shape of human skulls from
different sources using photographs taken in norma lateralis. One part was
obtained through a standardized protocol while the other part was obtained
from published pictures (with permissions) which were obtained using
different protocols. I have traditional measurements for each skull for the
published data set in order to compute the centroid size. However, taking
into account some theoretical issues I feel that such comparison may be
biased especially regarding size (i.e. CS) because both sets of images were
obtained using different distances between the camera and the target. In
order to minimize the size bias I plan to digitize landmarks and
semilandmarks only along the skull contour given that its shape can be
optimally characterized using a 2D approach. The location of landmarks in
other structures poorly characterized from the 2D approach (i.e distinct to
the contour) would increase the size bias. I will do a procrustes analysis
using both data sets and through a multivariate regression of size on the
procustes coordinates I will obtain residuals (i.e. shape variables). To my
knowledge using this approach I will minimize the size bias mentioned.
Obviously I will not use the centroid size in any subsequent analysis, only
the shape variables. Does anyone tell me if this approach is right? Some
suggestions?
thanks in advance

cheers
Pablo


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Re: [MORPHMET] Crowdsourced GM Bibliography

2016-03-09 Thread Carmelo Fruciano
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--
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Australia

Honorary Fellow - University of Catania - Catania, Italy
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http://www.fruciano.it/research/

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Re: [MORPHMET] Sliding Semilandmarks

2016-02-18 Thread Carmelo Fruciano

Ariadne Schulz <ariadne.sch...@gmail.com> ha scritto:


Hello all,

I'm having a bit of a semilandmark problem. I'm working on 3D surfaces with
semilandmarks. (Profuse thank yous to Emma for writing the scripts for
that.) The issue I'm having I think is occurring in the sliding. When I do
populations alone everything seems normal. The semilandmarks do not appear
to be going off the surface defined for them, but if I try to do more than
one population at once several of the semilandmarks slide off the surface
so my PCs get rather distorted. Based on the few individuals from different
populations I've looked at I think I do have interpopulation variation but
I wouldn't expect that to influence the sliding of semilandmarks. Has
anyone else encountered an issue like this with either 2D or 3D
semilandmarks? As with all things R I expect the answer will be something
like me omitting a comma somewhere so any suggestions you might have are
welcome.


Dear Ari,
to elaborate on what others have written, perhaps you also want to try  
and see how/if changing the criterion for sliding (minimizing bending  
energy vs minimizing Procrustes distance) and the number of iterations  
changes the results of your superimposition.


A post/discussion that may be interesting to you can be found at  
Stephan Schlager's blog:

http://zarquon42b.github.io/2014/11/07/ProcDSliding/

Best,
Carmelo




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Honorary Fellow - University of Catania - Catania, Italy
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http://www.fruciano.it/research/

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Re: [MORPHMET] testing for allometry in tpsRegr

2015-12-20 Thread Carmelo Fruciano

Elahep  ha scritto:




Hi morphometricians,


I have a data set consists of 7 landmarks and 7 semi-landmarks on the
carapace of a crab and I want to control my data for the effect of
allometry with tpsRegr. I am not sure which dataset should I use as
dependent variable (presence of semi-landmarks confused me in choosing the
correct dataset as dependent variable!):


   1. 1-TPS file consists of landmarks and semi-landmarks *before*
   removing the control lines
   2. 2- TPS file consists of landmarks and semi-landmarks *after* removing
   the control lines
   3. 3-   TPS file consists of superimposed landmarks and semi-landmarks
   (= *Procrustes coordinates*)


Would you please help me with this question?


Dear Elahep,
not sure what you mean with "control lines".

The procedure one generally uses when dealing with semilandmarks is to  
perform a generalized Procrustes analysis with sliding of  
semilandmarks (typically in tpsRelw), export the aligned coordinates  
(and the centroid size, if you want to use that as a measure of body  
size) and then treat the exported coordinates as if they were landmarks.
In your case, then, I would imagine you would use in tpsRegr the  
aligned coordinates and the centroid size previously exported from  
tpsRelw.


Another thing you might want to consider in the process is if your  
configuration of landmarks (or, rather, the biological structure  
you're trying to capture with them) is symmetric and, if so, if  
asymmetry is of interest for you...


Best,
Carmelo


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Re: [MORPHMET] Importing Data from Landmark Editor into MorphoJ

2015-11-25 Thread Carmelo Fruciano

Dear Jay,
the text file, as in the link you provided and copied to a text  
editor, contained a mixture of double spaces and tabs. For instance,  
already in the first line you have a tab between the ID and the first  
coordinate but two spaces between the first and the second coordinate.
Transforming it to just tabs gives me a file that I can open in  
MorphoJ (see attachment).

I hope this helps,
Carmelo

Jay Devine  ha scritto:


Hello, morphometrics community!

I have been trying to import a set of 3D landmarks generated in  
Landmark Editor into MorphoJ. Unfortunately, MorphoJ is having a  
hard time recognizing the file.


The error message I usually get goes as follows:

The number of lines with data: 0
is not the same as
the number of lines in the file: 24.
Check for empty lines in the data file (lines with just spaces or tab
stops, commas, etc.).
Another possible reason are text entries other than just the identifier
(classifiers must be imported from a separate file).

It seems like the program can not recognize my landmark data for  
some reason. I have made sure that every value is tab-separated, so  
I am not sure what is wrong. In addition, I have tried using commas  
to separate my values, and I have tried removing scientific notation  
(even though Klingenberg's guide says it is perfectly fine to use).


Here is a link to the data I'm using if you guys have time to take a  
peek: http://textuploader.com/5cbx8


The format looks a bit strange on there, but if you copy and paste  
the values into notepad it looks fine.


Thank you so much, in advance, for your time and help.

Jay





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NP743F  2.7826988e+001  1.2373236e+002  8.0533258e+002  3.1943138e+001  
1.3673395e+002  8.1580353e+002  1.7265701e+001  1.3429872e+002  7.9437695e+002  
1.2818111e+001  1.3600449e+002  7.8245886e+002  4.8344917e+001  1.3695609e+002  
8.2124213e+002  3.5336891e+001  1.2775404e+002  7.9681201e+002  2.1978477e+001  
1.1627573e+002  7.9611090e+002  3.4814217e+001  1.4557973e+002  7.8010278e+002  
2.3085680e+001  1.4887016e+002  7.9521021e+002  4.4295250e+001  1.4355661e+002  
7.9386426e+002  3.3886688e+001  1.4530602e+002  8.1331885e+002  5.6020599e+001  
1.4387912e+002  8.1044006e+002
NP301M  4.5620728e-001  6.9425400e+001  8.0141583e+002  5.4913330e+000  
8.3091423e+001  8.0831348e+002  -9.9645309e+000 7.7325432e+001  7.8965454e+002  
-1.0561714e+001 7.5987816e+001  7.7999866e+002  1.1844873e+001  7.8188560e+001  
8.1515863e+002  -3.4623718e+000 6.6013275e+001  7.8753815e+002  5.2797089e+000  
7.1658234e+001  7.9275952e+002  3.9035869e+000  8.7344589e+001  7.7715839e+002  
-5.8766489e+000 9.1613571e+001  7.8984064e+002  1.4034074e+001  8.7614426e+001  
7.8941150e+002  6.6685891e+000  9.0963966e+001  8.0515497e+002  2.4624598e+001  
8.8921684e+001  8.0260901e+002
NP249F  -3.5087891e+000 6.8961517e+001  8.0052972e+002  -1.8463974e+000 
8.2192993e+001  8.1088104e+002  -9.5408173e+000 7.4394707e+001  7.8764960e+002  
-8.9323864e+000 7.1146797e+001  7.8113654e+002  1.0354736e+001  8.6008087e+001  
8.1881555e+002  -4.9558945e+000 6.0961048e+001  7.9065649e+002  5.1675034e+000  
7.2170395e+001  7.9554639e+002  7.0143557e+000  8.7484131e+001  7.8003204e+002  
-6.8677964e+000 8.9034836e+001  7.8890033e+002  1.2767838e+001  8.8231178e+001  
7.9333478e+002  2.9530144e-001  9.1278915e+001  8.0681946e+002  1.8882383e+001  
9.0653732e+001  8.0865082e+002
NP248F  5.1288605e+000  -8.7091019e+001 7.8995001e+002  -2.8275299e+000 
-9.7629051e+001 7.8157678e+002  1.3520813e+001  -1.0104108e+002 8.0029688e+002  
2.1688499e+001  -1.0664723e+002 8.1317883e+002  -4.6516228e+000 -9.5386749e+001 
7.6205298e+002  1.7502426e+001  -7.7447197e+001 8.0022607e+002  1.8675446e+001  
-8.9019508e+001 7.8562018e+002  3.3282276e+001  -1.1282319e+002 7.8514093e+002  
1.0592249e+001  -1.1373569e+002 7.9756805e+002  2.2300182e+001  -1.0844306e+002 
7.7310809e+002  -1.3357821e+000 -1.0984053e+002 7.7937219e+002  8.6929626e+000  
-1.0629659e+002 7.5754163e+002
NP246M  1.8274155e+000  1.4089882e+002  7.7875909e+002  8.6824036e+000  
1.5441203e+002  7.8491943e+002  -8.3138504e+000 1.5258864e+002  7.754e+002  
-1.8895782e+001 1.5341078e+002  7.5584753e+002  2.5878700e+001  1.5408521e+002  
7.9149512e+002  -3.5585022e+000 1.3135515e+002  7.6487561e+002  8.9874191e+000  
1.4314792e+002  7.6586499e+002  3.2951097e+000  1.6381271e+002  

Re: [MORPHMET] how create nexux file for phylogeny in MorphoJ

2015-10-27 Thread Carmelo Fruciano

Dear Alaettin,
to my knowledge, MorphoJ does NOT perform cluster analysis (have a  
look at  
http://www.flywings.org.uk/MorphoJ_guide/frameset.htm?comparison/mapPhylo.htm  
).


Nexus files are reflective of a phylogenetic hypothesis and are  
normally obtained from programs that use methods of phylogenetic  
inference.
If one had a specific phylogenetic hypothesis in mind, one could also  
create the Nexus file by hand (i.e. in a text editor such as Notepad  
in Windows) following the format (of which there are some variants).

A formal description of the format can be found in
Maddison et al. 1997 Systematic Biology 46(4):590-621. (you can freely  
access the paper at http://www.phylo.org/tools/nexus_document.pdf ).
Various primers on the format are also available online (for instance  
at  
http://hydrodictyon.eeb.uconn.edu/eebedia/index.php/Phylogenetics:_NEXUS_Format  
).
In this case, you might want to know that trees are encoded in the  
Newick format (which is described, for instance, at  
http://evolution.genetics.washington.edu/phylip/newicktree.html )


I hope this helps,
Carmelo





Alaaettin Kaya <altkay...@gmail.com> ha scritto:


Dear
I want to do cluster analysis by morphoJ, but ı can't manage to create
nexux file. How is it create
thanks all

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Dicle University, Science Faculty
Biology Departmant
21280 DİYARBAKIR/TURKEY

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Re: [MORPHMET] question Elliptic Fourier Descriptors

2015-10-26 Thread Carmelo Fruciano

Dear Jens,
you might want to consider working with multivariate analyses (i.e.  
using all PCs and not a single one) and, as it has been suggested,  
using (multivariate) linear models rather than dividing scores by your  
size measure.

Best,
Carmelo


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Jens De meyer <demeyerjen...@gmail.com> ha scritto:


Dear,

I have a question about EFDs, and was wondering if you could help  
me? I have performed a PCA on standardized EFDs (standardized for  
first harmonic, using SHAPE-software). The EFDs represented head  
shapes of eels which were given different diets (we compared three  
different diets). The results of the PCA indicated that PC1 was  
related to variation in head width, with high PC-scores being  
related to broader heads and vice versa. Next, we performed a linear  
regression on these PC-scores and log(length) of the three different  
diets and observed a size-effect in all three diets.
Because of this, I wanted to divide the PC-scores by the total  
length of the studied eels. Then, we would perform an ANOVA on these  
length-corrected PC-scores between the different diets, as this  
would allow us to find out whether the mean head width of a certain  
diet is significantly broader than another diet.
Therefore, my question to you is: Am I acutally allowed to divide  
these PC-scores by total length?

Many thanks in advance!
Kind regards,
Jens De Meyer

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Re: [MORPHMET] Appending TPS files

2015-10-20 Thread Carmelo Fruciano


Daniel Svozil <dpsvo...@gmail.com> ha scritto:


Hi All,

So I am facing a dilemma, where I have digitized landmarks on 90
individuals, for each of 11 populations. The images and the associated TPS
file for each population is located in a separate folder (i.e. one folder
per population).

Now, I want to combine the TPS files from each population, into one single
TPS file. Is this possible? If so, how do I do it?

I have tried clicking append, (File>Save data>Append) in TPS Dig2, as well
as the Append files option in the drop down menu of TPS Util. In both
cases, I get the dialog box, where it asks for an input directory and an
output directory, however, no option to select multiple TPS files is
available.

It occurred to me that perhaps the separate TPS files had to be located in
the same folder, (I did not check the "include path" option when I created
each individual TPS file), but even so, when I repeat the Append files
steps listed above, I am still presented with the input/output directory
options and only the one TPS that was originally associated with that
folder (i.e. pop1 TPS file is the only one available in the pop1 directory,
even though I have copied the pop2 TPS file and images over, as well).

Any suggestions? Or will I have to start over with a TPS file containing
all images from all the populations as one?


Hi Daniel,
I guess you could simply try copying/pasting all the files together.  
This doesn't update the ID field but it didn't give me any problem in  
a quick check I did on another package of the tps series. How do you  
do this depends on your operating system and preferences. Under the  
command prompt in windows you can just type

copy *.TPS all.TPS
to append all the TPS files (in alphabetical order) in a single file  
called all.TPS.
Other solutions (importing in R, combining and then exporting) might  
be more elegant, though...

Best,
Carmelo


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Re: [MORPHMET] How to include new specimens in TPSdig and information on EDMA software

2015-07-07 Thread Carmelo Fruciano

Dear Miguel,
about the TPS question, I guess that the easiest is to create a new  
TPS file in tpsUtil and then use the function Append files in the  
same program to combine the old and the new file.

Best,
Carmelo


Miguel Eduardo Delgado Burbano mdelgadoburb...@gmail.com ha scritto:


Dear morphometricians

I have a couple of quite simple questions

1)  Once one has digitized a set on landmarks/semilandmarks in a series of
photographs it is possible to include new specimens?. I mean, if I have a
digitized dataset and I want to include new specimens it is possible?. I
tried but I only found the way to exclude specimens/individuals and/or
landmarks in TPSdig2 and TPSutil.

2) I want to know if there exists a new version of EDMA software. I want to
run analyses in EDMA but in PCs with updated versions of windows (7 and 8)
the old version of WindEDMA may present some incompatibilities.


thanks in advance
cheers

Miguel

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Re: [MORPHMET] comparison of RV values

2015-06-28 Thread Carmelo Fruciano

Patrick Arnold patrick.arn...@uni-jena.de ha scritto:


Dear all,

I am looking for patterns of integration between 3 substructures. I  
subjected the procrustes variables to pair-wise PLS analyses and  
received 3 RV values. Does the highest RV value correspond to the  
strongest integration or are RVs from different PLSs not comparable?  
Is their any possibility to perform a PLS on 3 structures  
simultaneously?



Dear Patrick,
yes, there are approaches to perform PLS on multiple blocks (see  
Bookstein et al. 2003 - Journal of Human Evolution; also search for  
multi-block PLS). A multi-set RV coefficient has been also proposed  
by Klingenberg (2009 - Evolution and Development) as the average of  
the pairwise RV coefficients.


The value of the RV coefficient also depends on sample size (Fruciano  
et al. 2013 - PLoS One) so comparisons of the value itself across  
datasets with different number of observations are inappropriate,  
unless this is taken into account (please, see the paper for details).


Please, also note that, although you might find them mentioned  
together for convenience, partial least squares analysis and the  
Escoufier RV coefficient are distinct things.


Best,
Carmelo



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Re: [MORPHMET] 2D Capture Protocol for mostly 2D specimens

2015-06-08 Thread Carmelo Fruciano

Zack Daugherty zackdaughe...@gmail.com ha scritto:



Hello all,

This is my first time wading into geometric mophometry as a PhD candidate.

First off the project:
I plan to track geometric morphometry data of Nassau grouper we have raised
in the lab.  There are some 130 juveniles that are now capable of being
anesthetized and handled.  I plan to gather data down to the individual
level for this cohort monthly to establish data on individual ontogenetic
trajectories.  But I have some questions regarding 2D capture, because *once
I start this there is no going back*.  The welfare of these animals
supercedes the morphometry work I have planned (these fish will be used for
future broodstock at our aquaculture facility).

[cut]

Questions:
Any other protocols that people are aware of I should look at for digital
capture?


Dear Zack,
if I was you, I would also think about the advantages/disadvantages of  
anesthesia. I have used it in certain situations but, depending on  
what your downstream application and target speies are, sometimes one  
can get away with not anestesizing fish (certain species, especially  
when raised in captive conditions, even let you pin  them to extend  
their fins). Considering that you stated that welfare of the fish is  
particularly important for you, that's the first thing that came to  
mind.


Also, this is probably very obvious, pay attention to keeping the fish  
straight (i.e. limit dorso-ventral arching). This kind of artifact  
will still probably present in your data, but it's good to try  
limiting it at its source. Your fish species is not extremely  
elongated so it's probably not going to be a very strong problem.



Should I surround my specimens in black material?


In my opinion, probably not if they are mostly grey as the specimen in  
the picture...



Should I purchase any white balance card sets?


I guess it depends how important is color to you...


Would a grid backdrop be neccessary for every photo behind the specimen or
just to initially calibrate a field a view before photographing specimens?


In my opinion, the most important part is having some sort of scale in  
the picture, possibly not too far from the specimen.


Well, that's my two cents, I hope this helps...
Best,
Carmelo



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Re: [MORPHMET] save trace of linear measurement on photo image

2015-05-28 Thread Carmelo Fruciano

Dear Caroline,
if I understood correctly what you need, I guess you have two options:
- in tpsDig2 the Save screen as... option in the File menu
- to print your current screen (under Windows normally you have a  
Stamp key in the keyboard)

Best,
Carmelo

Caroline Judy caroline.duf...@gmail.com ha scritto:


Dear MORPHMET group,

I am a new user of the program tpsDIG2, and have a general question that I
hope you can help me address.

I need to make a linear measurement of a single character on a series of
specimen photographs. I have set the scale bar and made the measurement for
several of the specimens, and I see that the measurement for each gets
added to the tps file. However, I would like to save  an image of the the
trace of the measurement (i.e. the black line) on the photograph, so I can
have a permanent record of how the measurement was made. This black line
does not appear to save on the image file - when I click to the next
specimen, and then go back to the original specimen, the trace is gone.

Is there a way to save the image of the measurement's trace? Or, is there a
better way to save a (visual) record of a linear measurement?

Thanks very much for any help!

Caroline D. Judy, PhD candidate
Louisiana State University

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e-mail c.fruci...@unict.it
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Re: [MORPHMET] Extracting Individual Mahalanobis Distances

2015-05-06 Thread Carmelo Fruciano

Dear Oliver,
if I understood correctly your question, I have a feeling you cannot  
do that in MorphoJ. There are probably ways to do it in R/Mablab.
However, again if I understood correctly your question, what you want  
to test is perhaps best accomplished with a linear model (and similar  
approaches) including a term for the interaction between treatment and  
fish group.

Best,
Carmelo



oliverhoo...@prstatistics.co.uk ha scritto:

I am currently trying to test the degree of difference (measured as  
a Mahalanobis distance) between two groups.


To give some background I have 2 groups of fish that differ in their  
life history strategy (groups A and B), these two groups have then  
been exposed to different conditions to induce a phenotypic response  
(conditions 1 and 2). I have then compared these groups in MorphoJ  
using a single canonical variate analysis.


The out put gives me a Mahalanobis distance for all comparisons but  
the ones I am interested in are for fish group A1 and A2 and for the  
fish group B1 and B2.


The question I want to answer is one group more plastic in their  
response to the 2 different conditions - So I need to test if the  
Mahalanobis distance between A1 and A2 fish is significantly more,  
less or not significant than the Mahalanobis distance between B1 and  
B2, fish but there is no variation around the Mahalanobis distance  
to allow a test..


Is there a way of extracting all the Mahlanobis distances for each  
individual from MorphoJ so I can then test these in a linear model  
or equivalent?


Or does anyone know a way of doing this?

Thanks in advance
Oliver Hooker
PR~Statistics

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Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

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Re: [MORPHMET] Testing for sexual dimorphism

2015-04-29 Thread Carmelo Fruciano

Dear Alex,
I imagine most people would consider MAN(C)OVA and/or permutation  
tests for difference in multivariate means as the typical approach.  
Obviously, the choice of methods might also depend on the design and  
research question. There is a chance that with 10 observations per sex  
you might have limited statistical power when comparing within each  
species.

Best,
Carmelo


Bjarnason, Alexander a.bjarna...@ucl.ac.uk ha scritto:


Dear morphometricians,
I have an interesting GMM dataset based on the cranial morphology of  
adult New World monkeys (platyrrhines) with a wide sampling of  
genera and species. I have approximately ten male and ten females  
for each species, and am interested in testing for size and shape  
dimorphism in each group. My current thinking is to use a Procrustes  
ANOVA to test for significant differences between males and females  
for each taxa, and wanted to enquire whether this was the standard  
approach with geometric morphometric data, or if an alternative  
approach would be more appropriate?

Any advice greatly appreciated,
Best wishes
Alex Bjarnason

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Re: [MORPHMET] MANOVA and shape data

2015-02-18 Thread Carmelo Fruciano

Dear all,
as an addendum to my previous message on tests for multivariate  
normality, I've just noticed that a new R package for this (MVN by  
Korkmaz et al 2014 -  
http://journal.r-project.org/archive/2014-2/korkmaz-goksuluk-zararsiz.pdf ) is  
out.

Best,
Carmelo

--
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Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/





Carmelo Fruciano c.fruci...@unict.it ha scritto:


Patrick Arnold patrick.arn...@uni-jena.de ha scritto:


Dear morphometrics,

I have two questions about applying MANOVA on shape data:

1. MANOVA assumes the data to be normal distributed. What is the  
best way to test normal distribution of multivariate shape data?  
And what is the best (free) software for this issue (is this  
embedded in PAST)?


Dear Patrick,
I normally use other software. However, it looks like PAST has some  
option for this at page 100 of the manual. On the other hand, you  
might want (also given the small sample sizes you mention below) to  
use resampling-based approaches...



2. The differences between my groups are very distinct in the CVA.


This is quite normal and well known (i.e. the fact that CVA shows  
often very clear separation of the groups). A detailed discussion of  
this can be found in


Mitteroecker, P. and F. Bookstein (2011). Linear Discrimination,  
Ordination, and the Visualization of Selection Gradients in Modern  
Morphometrics. Evolutionary Biology 38(1): 100-114.


Most importantly, Mitteroecker  Bookstein suggest using  
between-group principal component analysis as an alternative  
ordination technique. This is gaining popularity over time and, in  
my experience, it has been useful already in multiple cases  
(Franchini, Fruciano et al. 2014 - Molecular Ecology; Fruciano et  
al. 2014 - Biological Journal of the Linnean Society).


I want to test whether these differences are statistically  
significant, too. As my sample size only slightly exceeds the  
degrees of freedom, I want to apply the MANOVA onto the CVs (i.e.  
decrease in the number of dependent variables). Is this possible or  
is it redundant?


Although I have seen it done, I don't think this is a very good  
idea, as you have already suspected. Again, maybe resampling-based  
approaches might be a better choice (while, as Andrea Cardini was  
suggesting in some previous post, also recognizing the limitations  
of one's analysis).


I hope this helps,
Carmelo


--
Carmelo Fruciano
Marie Curie Fellow - University of Konstanz - Konstanz, Germany
Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/





--
Carmelo Fruciano
Marie Curie Fellow - University of Konstanz - Konstanz, Germany
Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

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Re: [MORPHMET] Ontogenetic changes in morphology

2015-02-17 Thread Carmelo Fruciano

Hi Adeline,
I'm not sure if this helps with your problems, but what you are  
describing reminds me of two things:


- MANCOVA using shape variables as dependent, species as categorical  
predictor and size (either of the claw or of the body) as covariate  
and testing not only for the main effects but also for the interaction  
between species and size


- So called relative warps in size-shape space (Mitteroecker et al  
2004 - J Hum Evol), which I personally used on some fish (Fruciano et  
al 2012 - Env Biol Fish), and can be used in your case as an  
exploratory tool to see if and where there is an abrupt change in  
the trajectory of each species


I am not sure how plotting claw size on body size would help you with  
shape, although maybe that's useful to find how much different  
descriptors of size are consistent with each other.


I hope this helps.
Best,
Carmelo



Adeline Yong adeline.yon...@gmail.com ha scritto:


Hi Everyone,

I am exploring the use of GMM to study the ontogenetic changes of claw
morphology in one species of crabs. The tips of the crab claws changes in
curvature (shape) as they grow and there are distinct differences if I
compare the claws of the juvenile crabs and the adults. However, the
intermediate stages are not so obvious. Crabs of various sizes (age) were
collected from two populations and I would like to determine the size when
the change in tip curvature most likely starts for each population. All the
major claws of each crab were photographed and landmarks were placed at the
homologous points of the claws. Semi-landmarks were used for the claw tips
as there were no homologous points along the curvature.  ln centrold size
of each individual claw was computed and plotted against body size
(carapace width) of the crabs.  I am not sure if I am approaching this the
correct way. Any help would be appreciated.

Thanks in advance.

Adeline

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--
Carmelo Fruciano
Marie Curie Fellow - University of Konstanz - Konstanz, Germany
Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

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Re: [MORPHMET] Warped Grids in MorphoJ

2015-02-13 Thread Carmelo Fruciano

Hi Michael,
if I understood correctly your question, I would do the following:
- Average replicates by specimen (I assume you did this to reduce  
measurement error so you wanna take averages for each observation)  
using the Average observation by... function
- Use the DFA module to perform a discriminant analysis using a  
classifier for dataset as grouping variable. One of the graphs is a  
diagram with the shape difference between the two group means (quoted  
from MorphoJ user guide)

Again, not sure if I interpreted correctly your question...
I hope this helps,
Carmelo




Michael Holmes mhol...@berkeley.edu ha scritto:


Hi All,
I am running MorphoJ on Mac OSX. I am looking at morhological variation
between two datasets. In each dataset, each specimen has four replicates. I
combined the datasets, made classifier files and ran the Procrustes fit and
generated the covariance matrix.  How then do I make a vector diagram/warp
grid that visualizes shape change between the average shape of the two
datasets? Thanks in advance for your help.

Mike


Michael W. Holmes

Ph.D. Candidate
University of California, Berkeley
Advisors: Dr. Rauri Bowie, Dr. Eileen Lacey

Museum of Vertebrate Zoology
3101 Valley Life Sciences Building
University of California
Berkeley, CA   94720  USA

http://ib.berkeley.edu/labs/lacey/holmes2.html

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--
Carmelo Fruciano
Marie Curie Fellow - University of Konstanz - Konstanz, Germany
Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

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Re: [MORPHMET] MANOVA and shape data

2015-02-08 Thread Carmelo Fruciano

Patrick Arnold patrick.arn...@uni-jena.de ha scritto:


Dear morphometrics,

I have two questions about applying MANOVA on shape data:

1. MANOVA assumes the data to be normal distributed. What is the  
best way to test normal distribution of multivariate shape data? And  
what is the best (free) software for this issue (is this embedded in  
PAST)?


Dear Patrick,
I normally use other software. However, it looks like PAST has some  
option for this at page 100 of the manual. On the other hand, you  
might want (also given the small sample sizes you mention below) to  
use resampling-based approaches...



2. The differences between my groups are very distinct in the CVA.


This is quite normal and well known (i.e. the fact that CVA shows  
often very clear separation of the groups). A detailed discussion of  
this can be found in


Mitteroecker, P. and F. Bookstein (2011). Linear Discrimination,  
Ordination, and the Visualization of Selection Gradients in Modern  
Morphometrics. Evolutionary Biology 38(1): 100-114.


Most importantly, Mitteroecker  Bookstein suggest using between-group  
principal component analysis as an alternative ordination technique.  
This is gaining popularity over time and, in my experience, it has  
been useful already in multiple cases (Franchini, Fruciano et al. 2014  
- Molecular Ecology; Fruciano et al. 2014 - Biological Journal of the  
Linnean Society).


I want to test whether these differences are statistically  
significant, too. As my sample size only slightly exceeds the  
degrees of freedom, I want to apply the MANOVA onto the CVs (i.e.  
decrease in the number of dependent variables). Is this possible or  
is it redundant?


Although I have seen it done, I don't think this is a very good idea,  
as you have already suspected. Again, maybe resampling-based  
approaches might be a better choice (while, as Andrea Cardini was  
suggesting in some previous post, also recognizing the limitations of  
one's analysis).


I hope this helps,
Carmelo


--
Carmelo Fruciano
Marie Curie Fellow - University of Konstanz - Konstanz, Germany
Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

--
MORPHMET may be accessed via its webpage at http://www.morphometrics.org

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Re: [MORPHMET] high-throughput 2D scanning using photo-scanner

2015-02-05 Thread Carmelo Fruciano

Dear Henry,
in addition to what Andrea suggested, I should mention that flatbed  
scanners have been already used also on fish and there are papers  
published on this.

An example is:
Herler, J., et al. (2007). A simple technique for digital imaging of  
live and preserved small fish specimens. Cybium 31(1): 39-44.

Best,
Carmelo

henry wallace henry.ee.wall...@gmail.com ha scritto:


I am contemplating a project involving small insects.  Data would be pixel
areas or distances of head, thorax, abdomen.  2D measurements.  Large
numbers of specimens required.

With appendages removed, the insects would be mounted on a flat surface,
such as poster board or paper, which is then scanned using a desktop
scanner (photo-scanner).  Dozens could be scanned at single time and the
resulting images can be cropped for data gathering.

Was just wanting initial reactions and/or recommendations on the approach.

H.

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--
Carmelo Fruciano
Marie Curie Fellow - University of Konstanz - Konstanz, Germany
Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

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Re: [MORPHMET] Tests on allometry pattern of several groups

2014-11-07 Thread Carmelo Fruciano

Hai-Jun SU suhaijun@gmail.com ha scritto:


Dear all,

Glad to be a part in this group.


Dear SU,
I'm not sure I fully understand your situation so please forgive me if  
I don't address your questions properly.



I am SU from Insubria Univeristy of Italy now, at present, I am trying to
use GMM to analyze the squirrel mandibular morph to distinguish three
geographic populations (to test how similar they are), at two levels, i.e.
Ind and FA. When I want to investigate if they were similar allometry
pattern using MANCOVA, I got a problem, the results of MANCOVA (both
results by SPSS and TpsRegr, and the shape data were superimposed as a
subset separately)showed extremely significant, but from the regression
plots and their slopes values( were 0.27, 0.31 and 0.34 respectively, from
fitting of regression scores and Log CS ), it seemed similar slopes and
easy to centered, so, my puzzles are:
1)  Should I believe in these results? did it really mean they can't be
forced to parallel slopes?
2) If yes, does it mean that I can't make the regression for 3 populations
together in MorphoJ ( including with and without pooling within group) ,
i.e. I have to make the allometry-related regression analysis in separate
populations (superimposed separately) in the next steps?


I'm not sure which tests you exactly did. I guess that performing a  
MANCOVA (testing for both the population and size effects and their  
interaction) in a general-purpose statistical software (SPSS) and/or  
performing the procedure suggested in the TPSRegr help (test for  
common slopes) would be the way to go to know if you can perform a  
single regression or not.



3) When I was using TpsRegr, I imported the NTS file got from TpsDig, but
it contained all observations of pictures, not individuals, so how can I
use TpsRegr with averaged individuals (procrustes coordinates and Log CS
values) ? what's the differences between them?


I guess the easiest, if you're using MorphoJ and you have some  
identifier that identifies each specimen, is to average them in  
MorphoJ, then export the averaged shapes and CS (or logCS) and finally  
convert the file in a text editor to NTS format (which, given how  
simple is the NTS format for use in the TPS series, is easily done).  
Of course, you can also compute average shapes after superimposition  
in other software (such as Excel) but this might be more time consuming.


I hope this helps.
Best,
Carmelo


--
Carmelo Fruciano
Marie Curie Fellow - University of Konstanz - Konstanz, Germany
Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

--
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Re: [MORPHMET] Adjusting permutted p-values in a DFA for morphometric analysis

2014-10-09 Thread Carmelo Fruciano

dthulman dthul...@gmail.com ha scritto:


Hello All,
I recently reviewed a paper in which the authors were analyzing artifact
shapes using landmarks-based geometric morphometrics. They performed a DFA
and permutted the data 1000 times. They then modified the critical values
before comparing the results using a correction to control for false
discovery rate.The formula is in:


Benjamini Y, Yekutieli D (2001) The control of the false discovery rate in
multiple testing under dependancy. Ann Stat 29:1165–1188.

I've not seen this used before and was wondering if it is appropriate in
DFA's for morphometric data. I've been evaluating the effectiveness of a
DFA using bootstrapping and a misallocation table and not relying on the
p-values.



Dear Dave,
that method (and others, related) is used widely in fields where one  
does a really large quantity of tests (microarray data is the  
classical example, with thousands of tests on per gene). The reason  
for this popularity is that it is much less conservative than other  
classical methods, such as the classical Bonferroni or the sequential  
Bonferroni (introduced by Holm 1979 Scand J Stat and later on  
popularized in evolutionary biology by Rice 1989 Evolution). With such  
large numbers of tests, using (sequential) Bonferroni adjustements  
would leave very few significant tests (if any).


Although I guess there should be no special problem in using the  
Benjamini Hochberg and related methods with morphometric data,  
normally morphometric studies do not perform so many tests (wether the  
p-value is obtained through resampling or not).


Just a couple of other comments:

- not everyone agrees on the necessity of corrections for multiple  
tests (see Perneger 1998 BMJ for a brief list of the reasons) and  
actually controlling for false discovery rate (as in Benjamini  
Hochberg and related methods) has been suggested as a possible way to  
reconcile different views about the necessity of corrections for  
multiple tests (see Garcia 2004 Oikos for a comment more or less along  
these lines)


- I guess that (cross-validated) classification rates in discriminant  
analysis and multivariate tests for difference in means, although  
somehow related, can still be thought to serve two different purposes  
so I personally don't think one should be abandoned in favour of the  
other


Best,
Carmelo



--
Carmelo Fruciano
Marie Curie Fellow - University of Konstanz - Konstanz, Germany
Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/

--
MORPHMET may be accessed via its webpage at http://www.morphometrics.org

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