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Scan, extract, wrap, compute—a 3D method to analyse morphological shape differences
Quantitative analysis of shape and form is critical in many biological disciplines, as context-dependent morphotypes reflect changes in gene expression and physiology, e.g., in comparisons of environment-dependent phenotypes, forward/reverse genetic assays or shape development during ontogenesis. 3D...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5995102/ https://www.ncbi.nlm.nih.gov/pubmed/29900069 http://dx.doi.org/10.7717/peerj.4861 |
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author | Horstmann, Martin Topham, Alexander T. Stamm, Petra Kruppert, Sebastian Colbourne, John K. Tollrian, Ralph Weiss, Linda C. |
author_facet | Horstmann, Martin Topham, Alexander T. Stamm, Petra Kruppert, Sebastian Colbourne, John K. Tollrian, Ralph Weiss, Linda C. |
author_sort | Horstmann, Martin |
collection | PubMed |
description | Quantitative analysis of shape and form is critical in many biological disciplines, as context-dependent morphotypes reflect changes in gene expression and physiology, e.g., in comparisons of environment-dependent phenotypes, forward/reverse genetic assays or shape development during ontogenesis. 3D-shape rendering methods produce models with arbitrarily numbered, and therefore non-comparable, mesh points. However, this prevents direct comparisons. We introduce a workflow that allows the generation of comparable 3D models based on several specimens. Translocations between points of modelled morphotypes are plotted as heat maps and statistically tested. With this workflow, we are able to detect, model and investigate the significance of shape and form alterations in all spatial dimensions, demonstrated with different morphotypes of the pond-dwelling microcrustacean Daphnia. Furthermore, it allows the detection even of inconspicuous morphological features that can be exported to programs for subsequent analysis, e.g., streamline- or finite-element analysis. |
format | Online Article Text |
id | pubmed-5995102 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-59951022018-06-13 Scan, extract, wrap, compute—a 3D method to analyse morphological shape differences Horstmann, Martin Topham, Alexander T. Stamm, Petra Kruppert, Sebastian Colbourne, John K. Tollrian, Ralph Weiss, Linda C. PeerJ Computational Biology Quantitative analysis of shape and form is critical in many biological disciplines, as context-dependent morphotypes reflect changes in gene expression and physiology, e.g., in comparisons of environment-dependent phenotypes, forward/reverse genetic assays or shape development during ontogenesis. 3D-shape rendering methods produce models with arbitrarily numbered, and therefore non-comparable, mesh points. However, this prevents direct comparisons. We introduce a workflow that allows the generation of comparable 3D models based on several specimens. Translocations between points of modelled morphotypes are plotted as heat maps and statistically tested. With this workflow, we are able to detect, model and investigate the significance of shape and form alterations in all spatial dimensions, demonstrated with different morphotypes of the pond-dwelling microcrustacean Daphnia. Furthermore, it allows the detection even of inconspicuous morphological features that can be exported to programs for subsequent analysis, e.g., streamline- or finite-element analysis. PeerJ Inc. 2018-06-08 /pmc/articles/PMC5995102/ /pubmed/29900069 http://dx.doi.org/10.7717/peerj.4861 Text en ©2018 Horstmann et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Computational Biology Horstmann, Martin Topham, Alexander T. Stamm, Petra Kruppert, Sebastian Colbourne, John K. Tollrian, Ralph Weiss, Linda C. Scan, extract, wrap, compute—a 3D method to analyse morphological shape differences |
title | Scan, extract, wrap, compute—a 3D method to analyse morphological shape differences |
title_full | Scan, extract, wrap, compute—a 3D method to analyse morphological shape differences |
title_fullStr | Scan, extract, wrap, compute—a 3D method to analyse morphological shape differences |
title_full_unstemmed | Scan, extract, wrap, compute—a 3D method to analyse morphological shape differences |
title_short | Scan, extract, wrap, compute—a 3D method to analyse morphological shape differences |
title_sort | scan, extract, wrap, compute—a 3d method to analyse morphological shape differences |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5995102/ https://www.ncbi.nlm.nih.gov/pubmed/29900069 http://dx.doi.org/10.7717/peerj.4861 |
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