Hi Murat,
Please clone the latest source code of shapeworks
( https://github.com/SCIInstitute/shapeworks) ... I have fixed this
issue ...you should be able now to get repeatable results with the
same set of shapes and parameters and with disabling openmp ...
you might want to try this first on a small subset of shape just
to make sure that it actually works ...
best regards
Shireen
On 02/17/2016 10:28 PM, Murat Maga wrote:
Hi
Shireen,
There
are few things going on I think.
First
off using the provided SW studio windows binary we get
repeatable results. But that’s not going to cut it for us,
because I have 500 samples. I don’t have windows box that
has the necessary amount of memory to run all the samples.
At about 200 samples, it is maxing out on my 32GB RAM.
Therefore
downloaded the latest linux commandline tool (from the
website links) and compiled it. We did not get repeatable
results with or without openMP enabled. When I execute the
script on the same samples with using the same parameter set
back to back, I get different results. I am not so concerned
that the exact correspondence is not achieved. What I am
concerned is if you rank them by their relative position to
their respective mean (from closest to farthest) based on
procrustes distance, ranking is not identical in those runs.
That is quite concerning, at least to me.
So
there is something we are missing in Linux causing the
inconsistency, but I can’t quite figure it out. I even
exported the groom and optimize xml files I used on windows
and try on Linux and that didn’t make any difference.
M
Hi,
1 . In order to get repeatable results, i.e same exact
correspondence model, you might want to disable openmp at
the expense of longer computation time ... nonetheless, with
openmp, you still get similar correspondence model in terms
of representation, yet not the same exact ordering and
positional information.
2. points in wpts are already procrustes aligned and can
directly be fed to PCA. we are working on an improved
version of SW and will add the exportation of the eigenmodes
and scores ... thanks for bringing this up ... for the time
being, please refer to ComputeModeLengths.cxx for utilities
that would compute pca modes and scores ...
hope this helps ...
best regards
Shireen
On 02/17/2016 12:07 PM, Murat Maga wrote:
Hi,
I
want to follow up on this. We want to use the PC scores
from the shapeworks analysis as input for our quantitative
trait mapping to find genomic intervals associated with
molar morphology and size. We successfully used this
approach using traditional landmarks, but I definitely see
value using SW. However, there are couple concerns:
1.
We
are not getting repeatable results (as Ryan described
below) with identical datasets and parameter xmls.
Parameter space is too big to randomly experiment on our
own. We can use suggestions on what to focus and what
might be driving this randomness.
2.
Although
I can visualize the modes of variation using SW Studio, I
can’t get to the individual eigenvectors or the PC scores.
To overcome this, I am feeding the wpts files into a
Procrustes analysis and doing alignment and PCA, which is
kind of silly, since SW does it already. It would be good
to expose the PC scores an eigenvectors.
Best
wishes,
Murat
A.
Murat Maga, PhD
Assistant
Professor
UW
Dept. of Pediatrics
Division
of Craniofacial Medicine
&
Member
Seattle
Children’s Research Institute
Center
for Developmental Biology and Regenerative Medicine
From:
shapeworks-users-request@sci.utah.edu [mailto:shapeworks-users-request@sci.utah.edu]
On Behalf Of Young, Ryan
Sent: Tuesday, February 16, 2016 3:14 PM
To: shapeworks-users@sci.utah.edu
Subject: [shapeworks-users] unstable shapeworks
results
Hello,
I have been using shapeworks to landmark six different
mouse molars. Shapeworks was run twice on each molar,
with identical parameters and volumes. The results are
surprisingly different. Regressing the distance to the
mean shape of each the landmarks configuration between
runs, 5-10 samples are drastically different. See
attached plot. I was wondering if I am running the
samples with enough iterations? I am going to
experiment with increasing the number of iteration to
see if the results stabilize, but would greatly
appreciate any suggestions. The top of the groom.xml
and run.xml files are below.
groom.xml
<?xml version="1.0" encoding="UTF-8"?>
<blur_sigma>0.5</blur_sigma>
<antialias_iterations>50</antialias_iterations>
<background>0</background>
<foreground>2</foreground>
<transform_file>/cm/shared/data/n2_molars/shapeworks/label1//shapeworks.transform</transform_file>
<inputs>/cm/shared/data/n2_molars/shapeworks/label1/def_152-11_to_atlas.nii.gz_inv.nii.gz
run.xml
<?xml version="1.0" encoding="UTF-8"?>
<iterations_per_split>100</iterations_per_split>
<starting_regularization>1000</starting_regularization>
<ending_regularization>0.1</ending_regularization>
<number_of_particles>1024</number_of_particles>
<optimization_iterations>1000</optimization_iterations>
<output_points_prefix>/cm/shared/data/n2_molars/shapeworks/label1//output_points</output_points_prefix>
<output_transform_file>/cm/shared/data/n2_molars/shapeworks/label1//output_transform_file</output_transform_file>
<inputs>/
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