Morpho and Rvcg – Shape Analysis in R: R-Packages for Geometric Morphometrics, Shape Analysis and Surface Manipulations
01 Jan 2017-pp 217-256
TL;DR: This tutorial gives an introduction into landmark/surface-mesh based statistical shape analysis in R – specifically using the packages Morpho and Rvcg.
Abstract: The mathematical/statistical software platform R has seen an immense increase in popularity within the last decade. Its main advantages are its flexibility, a large repository of freely available extensions, its open-source nature and a thriving community. This tutorial gives an introduction into landmark/surface-mesh based statistical shape analysis in R – specifically using the packages Morpho and Rvcg. Beginning with examples based on sparse sets of anatomical landmarks, the tutorial will go on dealing with surface and curve landmarks and more challenging tasks such as mesh manipulations and surface registration. Apart from statistical analyses, emphasis will also be put on comprehensive visualization of the results. Extensive examples and code snippets are provided to allow the reader to easily replicate the analyses.
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TL;DR: New functionality in the second major release of PlantCV includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.
Abstract: Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.
188 citations
Cites methods from "Morpho and Rvcg – Shape Analysis in..."
...The landmark functions in PlantCV output untransformed point values that can either be directly input into morphometric programs in R (shapes (Dryden & Mardia, 2016) or morpho (Schlager, 2017)) or uniformly rescaled to a 0-1 coordinate system using the PlantCV ‘scale_features’ function....
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TL;DR: High-resolution 3D quantification of skull shape with dense taxonomic sampling across a major vertebrate clade, birds, is combined to demonstrate that the avian skull is formed of multiple semi-independent regions that epitomize mosaic evolution, with cranial regions and major lineages evolving with distinct rates and modes.
Abstract: Mosaic evolution, which results from multiple influences shaping morphological traits and can lead to the presence of a mixture of ancestral and derived characteristics, has been frequently invoked in describing evolutionary patterns in birds. Mosaicism implies the hierarchical organization of organismal traits into semiautonomous subsets, or modules, which reflect differential genetic and developmental origins. Here, we analyze mosaic evolution in the avian skull using high-dimensional 3D surface morphometric data across a broad phylogenetic sample encompassing nearly all extant families. We find that the avian cranium is highly modular, consisting of seven independently evolving anatomical regions. The face and cranial vault evolve faster than other regions, showing several bursts of rapid evolution. Other modules evolve more slowly following an early burst. Both the evolutionary rate and disparity of skull modules are associated with their developmental origin, with regions derived from the anterior mandibular-stream cranial neural crest or from multiple embryonic cell populations evolving most quickly and into a greater variety of forms. Strong integration of traits is also associated with low evolutionary rate and low disparity. Individual clades are characterized by disparate evolutionary rates among cranial regions. For example, Psittaciformes (parrots) exhibit high evolutionary rates throughout the skull, but their close relatives, Falconiformes, exhibit rapid evolution in only the rostrum. Our dense sampling of cranial shape variation demonstrates that the bird skull has evolved in a mosaic fashion reflecting the developmental origins of cranial regions, with a semi-independent tempo and mode of evolution across phenotypic modules facilitating this hyperdiverse evolutionary radiation.
167 citations
TL;DR: Detailed comparative analyses of two fossil crania from Apidima Cave, Greece, indicate that two late Middle Pleistocene human groups were present at this site; first an early Homo sapiens population followed by a Neanderthal population.
Abstract: Two fossilized human crania (Apidima 1 and Apidima 2) from Apidima Cave, southern Greece, were discovered in the late 1970s but have remained enigmatic owing to their incomplete nature, taphonomic distortion and lack of archaeological context and chronology. Here we virtually reconstruct both crania, provide detailed comparative descriptions and analyses, and date them using U-series radiometric methods. Apidima 2 dates to more than 170 thousand years ago and has a Neanderthal-like morphological pattern. By contrast, Apidima 1 dates to more than 210 thousand years ago and presents a mixture of modern human and primitive features. These results suggest that two late Middle Pleistocene human groups were present at this site—an early Homo sapiens population, followed by a Neanderthal population. Our findings support multiple dispersals of early modern humans out of Africa, and highlight the complex demographic processes that characterized Pleistocene human evolution and modern human presence in southeast Europe. Detailed comparative analyses of two fossil crania from Apidima Cave, Greece, indicate that two late Middle Pleistocene human groups were present at this site; first an early Homo sapiens population followed by a Neanderthal population.
154 citations
TL;DR: The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community.
Abstract: To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse . The natverse allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community.
128 citations
Cites background or methods from "Morpho and Rvcg – Shape Analysis in..."
...Morphological clustering. https://elifesciences.org/articles/53350#video4 Video 5....
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...Its packages, neuromorphr,Xflycircuit,Xvfbr,Xmouselight,Xinsectbrainr and fishatlas can read from large repositories of neuron morphology data, many of which are co-registered in a standard brain space. neuromorphr provides an R client for the NeuroMorpho.org API (Ascoli et al., 2007; Halavi et al., 2008; Nanda et al., 2015), a curated inventory of reconstructed neurons (n = 107395, 60 different species) that is updated as new reconstructions are collected and published....
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...The natverse mainly operates with skeleton data, but the geometry of neuron mesh data can be analysed using the more general R packages Rvcg and Morpho (Schlager, 2017)....
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...Significantly, if an experimenter is able to register their functional imaging data to a template brain space (Mann et al., 2017; Pacheco et al., 2019), or alternatively identify neuroanatomical features in that data that can be used to build a landmark-based affine or thin-plate spline registration (e.g. using Morpho Schlager, 2017), they may be able to directly link it to cell types discovered in other datasets, including EM datasets....
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...It already hosts a wealth of packages for general morphometric and graph theoretic analysis (Csardi and Nepusz, 2006; Duong, 2007; Lafarge et al., 2014; Schlager, 2017)....
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TL;DR: Homo luzonensis is a new species of Homo from the Callao Cave in the Philippines from the Late Pleistocene epoch that displays a combination of primitive and derived morphological features that is different from the combination of features found in other species in the genus Homo.
Abstract: A hominin third metatarsal discovered in 2007 in Callao Cave (Northern Luzon, the Philippines) and dated to 67 thousand years ago provided the earliest direct evidence of a human presence in the Philippines. Analysis of this foot bone suggested that it belonged to the genus Homo, but to which species was unclear. Here we report the discovery of twelve additional hominin elements that represent at least three individuals that were found in the same stratigraphic layer of Callao Cave as the previously discovered metatarsal. These specimens display a combination of primitive and derived morphological features that is different from the combination of features found in other species in the genus Homo (including Homo floresiensis and Homo sapiens) and warrants their attribution to a new species, which we name Homo luzonensis. The presence of another and previously unknown hominin species east of the Wallace Line during the Late Pleistocene epoch underscores the importance of island Southeast Asia in the evolution of the genus Homo.
127 citations
References
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Journal Article•
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Abstract: Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team.
272,030 citations
Book•
23 Nov 2005TL;DR: The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics, and deals with the supervised learning problem for both regression and classification.
Abstract: A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.
11,357 citations
10,702 citations
TL;DR: The decomposition of deformations by principal warps is demonstrated and the method is extended to deal with curving edges between landmarks to aid the extraction of features for analysis, comparison, and diagnosis of biological and medical images.
Abstract: The decomposition of deformations by principal warps is demonstrated. The method is extended to deal with curving edges between landmarks. This formulation is related to other applications of splines current in computer vision. How they might aid in the extraction of features for analysis, comparison, and diagnosis of biological and medical images in indicated. >
5,065 citations
TL;DR: In this article, the principal axes of shape change for triangles and features of shape comparison are discussed. But the authors do not discuss the relationship between landmarks and shape coordinates of triangles.
Abstract: 1. Introduction 2. Preliminaries 3. Landmarks 4. Distance measures 5. Shape coordinates 6. Principal axes of shape change for triangles 7. Features of shape comparison 8. Retrospect and prospect.
3,131 citations