Re: [MORPHMET] Re: Open Access Repositories for GMM data and 3D models

[Ashleigh Haruda]

Dear all,

Thank you so much for your replies- they have all been incredibly helpful.
I'm really pleased to know that there are free archives to deposit data
which has given me much more wiggle room in my budgets. Do keep any
suggestions/comments/reviews coming. I'll be compiling a list/spreadsheet
for any that would like to keep track of these as well.

Many thanks MORPHMET!

Ashleigh

Ashleigh Haruda, Ph.D.

Ashleigh Haruda, Ph.D.


On Fri, Jan 20, 2017 at 9:15 PM, terrielsimmons 
wrote:

> Hi Ashleigh,
>
> The NIH 3D Print Exchange will take all kinds of 3D models, and associated
> files can be included in the zip (https://3dprint.nih.gov/discover). It's
> free to use and you can select the licensing, upload additional pics and
> info. Embodi3D started as a biomedical site, but the model categories have
> expanded into paleontology, anthropology, miscellaneous, and research (
> https://www.embodi3d.com/files/). You can also pick your licensing. No
> DOIs on these sites, although the NIH site has catalog numbers and at some
> point were planning to implement DOIs.
>
> For my own models, I am considering using Figshare to get a DOI for the
> collection and then using the above sites for the individual models.
>
> Terrie Simmons-Ehrhardt
>
> On Tuesday, January 17, 2017 at 11:49:54 AM UTC-5, ashleigh.haruda wrote:
>
>> Dear All,
>>
>> I've been investigating open access repositories to deposit both 3D
>> models as well as GMM data and have been struggling to find any which offer
>> built-in support and pricing for these types of data. I work mainly with
>> zooarchaeological specimens, so I am most familiar with archaeological
>> repositories such as Open Context and ADS. Does anyone have any other
>> suggestions for good open access sites? I'm particularly interested in
>> those which already have support in place, without having to create
>> customized plans for acquisition and pricing.
>>
>> Cheers,
>>
>> Ashleigh
>> Ashleigh Haruda, Ph.D.
>>
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[MORPHMET] Re: Open Access Repositories for GMM data and 3D models

[Zack Daugherty]

I have been using Open Science Framework https://osf.io/ which is a very 
user friendly platform in my dissertation work.  It also has the ability to 
mint DOIs.

Zack
Zack Daugherty, PhD Candidate
University of Miami


On Tuesday, January 17, 2017 at 11:49:54 AM UTC-5, ashleigh.haruda wrote:
>
> Dear All, 
>
> I've been investigating open access repositories to deposit both 3D models 
> as well as GMM data and have been struggling to find any which offer 
> built-in support and pricing for these types of data. I work mainly with 
> zooarchaeological specimens, so I am most familiar with archaeological 
> repositories such as Open Context and ADS. Does anyone have any other 
> suggestions for good open access sites? I'm particularly interested in 
> those which already have support in place, without having to create 
> customized plans for acquisition and pricing. 
>
> Cheers, 
>
> Ashleigh
> Ashleigh Haruda, Ph.D.
>

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Re: [MORPHMET] eliminating the effect of population differences

[David Katz]

Elahe and Ari,

If your dependent observations have more than a few dimensions, such as is
typical with landmark data or even a collections of linear measurements,
then I think the common covariance matrix recommendation from Dr. Rohlf is
the more standard approach. A typical strategy for removing group structure
is to perform your analysis on the pooled within group covariance matrix.
Chs.11 and 12 of Zelditch et al's *Geometric Morphometrics for Biologists*
provides an overview and citations, as well as the equation for
partitioning overall covariance into within and between group components.

However, Dr. Belk is correct that, in principle, a mixed model suits your
needs. The mixed model provides a way to partition random deviances
attributable to population history and structure from common (fixed)
effects of developmental stage and sex. You will have to think about how
you want to model conditionality of sexual dimorphism with respect to
stage. For example, if dimorphism does not arise until later stages of
development in your subject species, it does not make much sense to model a
single dimorphism coefficient across the entire sample.

To make the model go, you will need data with which to estimate pairwise
evolutionary relationships among the groups in your sample. The computation
of random effects depends upon it. Stone et al (http://rstb.
royalsocietypublishing.org/content/366/1569/1410) describe some of the
challenges of estimating relatedness where there is gene flow among the
sample clusters (i.e., where your groups are populations rather than
non-reticulating species). A paper from me+colleagues, linked to below,
provides an overly simple but (we think) reasonable solution to this.

This leaves one more potential problem: dimensionality. If the dependent
observation is univariate (centroid size, the first shape principal
component, etc.) or very low dimensional, the MCMCglmm package (see
http://onlinelibrary.wiley.com/doi/10./j.1420-9101.2009.01915.x/full)
could suit your mixed model needs. However, if your data is truly
multivariate (GM or anything more than a handful of linear measurements), I
would recommend looking at the BSFG package. We used it to estimate sex and
climate effects on the human cranium, using a subset of populations from
the Howells linear craniometric collection. You can find that paper on my
ResearchGate page (ResearchGate profile
). You will also find a
poster where we extend the application to cranial and mandibular 3D
landmark data. In the next few months, we should have a paper out that
combines high-dimensional mixed model analysis with 3DGM in a more
satisfying way than was managed in the poster.

Unfortunately, unless the developers have finished updating the BSFG
package, it is not quite plug and play. It takes some time to figure out.
You need familiarity with Bayesian analysis, and with Matlab. However, the
outputs are worth the effort. For example, with GM data, your fixed effect
posterior will estimate shape contrasts for sex and developmental stage
effects for the whole shape configuration, rather than on synthetic,
orthogonal subsets (PCs).

Conclusion: if your data is multidimensional and you don't think you can
get going with BSFG, for the time being, the common covariance matrix
approach is probably your best option.

David

On Thu, Jan 19, 2017 at 5:24 PM, Mark Belk  wrote:

What you describe – samples from multiple populations – is best considered
as a random effect in a typical generalized linear model format.  You have
randomly sampled some populations from all of those that might be
available.  If I understand your data correctly, to evaluate allometry, use
a mixed model approach where some trait measurement is the response
variable and some measure of body size would be the predictor variable,
then population would be included as a random effect in the model.  This
structure has the advantage of accounting for and adjusting for covariation
among populations before the fixed effect is evaluated.  Appropriately
crafted mixed models can rigorously account for a range of complicated
covariance structures within the context of one model.  Several examples of
the use of mixed models in ecology and evolution can be found in the
literature.

Hope that helps,



Mark



Mark C. Belk, Professor of Biology

Brigham Young University

Editor, *Western North American Naturalist*

801-422-4154 <(801)%20422-4154>



*From:* Ariadne Schulz [mailto:ariadne.sch...@gmail.com]
*Sent:* Wednesday, January 18, 2017 1:27 PM
*To:* Elahe
*Cc:* MORPHMET
*Subject:* Re: [MORPHMET] eliminating the effect of population differences



I would like to hear any responses to this as well. I did something similar
and I wasn't sure how to approach this question. In future studies I would
like to address precisely this issue. My inclination would be that first
you would want to determine how much morphological 

Re: [MORPHMET] Re: MeshLab - setting default FOV as Ortho?

[Antonio Profico]

Hi all,

to set the Ortho view in MeshLab: "shift" + "scroll down" (using middle
click). You can see the value on the left bottom.

Antonio

2017-01-20 16:17 GMT+01:00 terrielsimmons :

> Hi Christy,
>
> I don't think there's a way to set Ortho as the default view. I just
> change it with Windows --> View from... Meshlab 2016 has more options under
> this menu, for example, to select front with the z up, like CT scans. You
> can also hold shift and scroll the mouse wheel.
>
> Terrie
>
>
> On Thursday, January 19, 2017 at 9:23:09 PM UTC-5, Christy Hipsley wrote:
>>
>> Hi all,
>>
>> Does anyone know if it's possible to set the Field of View (FOV) in
>> MeshLab to Ortho as a default setting? It drives me nuts each time I open a
>> file to have to change it, and I don't know why anyone would work in
>> MeshLab without automatically changing this anyway. I've asked a couple of
>> other colleagues but no happy solution so far - I'm hoping someone here
>> might have the magic answer!
>>
>> Thanks,
>> Christy
>>
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-- 
__

Antonio Profico
PhD
Department of Environmental Biology – Dipartimento di Biologia Ambientale
SAPIENZA Università di Roma

Lab.  06 4991 2690
Mob. 3293440766

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[MORPHMET] Re: MeshLab - setting default FOV as Ortho?

[terrielsimmons]

Hi Christy,

I don't think there's a way to set Ortho as the default view. I just change 
it with Windows --> View from... Meshlab 2016 has more options under this 
menu, for example, to select front with the z up, like CT scans. You can 
also hold shift and scroll the mouse wheel.

Terrie

On Thursday, January 19, 2017 at 9:23:09 PM UTC-5, Christy Hipsley wrote:
>
> Hi all,
>
> Does anyone know if it's possible to set the Field of View (FOV) in 
> MeshLab to Ortho as a default setting? It drives me nuts each time I open a 
> file to have to change it, and I don't know why anyone would work in 
> MeshLab without automatically changing this anyway. I've asked a couple of 
> other colleagues but no happy solution so far - I'm hoping someone here 
> might have the magic answer!
>
> Thanks,
> Christy 
>

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