Discriminant analysis of principal components: a new method for the analysis of genetically structured populations

<p>Abstract</p> <p>Background</p> <p>The dramatic progress in sequencing technologies offers unprecedented prospects for deciphering the organization of natural populations in space and time. However, the size of the datasets generated also poses some daunting challenges. In particular, Bayesian clustering algorithms based on pre-defined population genetics models such as the STRUCTURE or BAPS software may not be able to cope with this unprecedented amount of data. Thus, there is a need for less computer-intensive approaches. Multivariate analyses seem particularly appealing as they are specifically devoted to extracting information from large datasets. Unfortunately, currently available multivariate methods still lack some essential features needed to study the genetic structure of natural populations.</p> <p>Results</p> <p>We introduce the <it>Discriminant Analysis of Principal Components </it>(DAPC), a multivariate method designed to identify and describe clusters of genetically related individuals. When group priors are lacking, DAPC uses sequential K-means and model selection to infer genetic clusters. Our approach allows extracting rich information from genetic data, providing assignment of individuals to groups, a visual assessment of between-population differentiation, and contribution of individual alleles to population structuring. We evaluate the performance of our method using simulated data, which were also analyzed using STRUCTURE as a benchmark. Additionally, we illustrate the method by analyzing microsatellite polymorphism in worldwide human populations and hemagglutinin gene sequence variation in seasonal influenza.</p> <p>Conclusions</p> <p>Analysis of simulated data revealed that our approach performs generally better than STRUCTURE at characterizing population subdivision. The tools implemented in DAPC for the identification of clusters and graphical representation of between-group structures allow to unravel complex population structures. Our approach is also faster than Bayesian clustering algorithms by several orders of magnitude, and may be applicable to a wider range of datasets.</p

Implémentation par automates cellulaires d'une modélisation architecturale de rétine biologique

Cet article traite de l'implémentation sur calculateur classique d'une modélisation cellulaire de la rétine biologique via deux mod`eles d'automates cellulaires (2D et 3D). Les algorithmes utilisés dans cet objectif, pénalisants en temps de calcul, nécessitent la plupart du temps une architecture de traitement spécifique et par conséquent, une adaptation de l'algorithme. Notre solution alternative utilise les fonctionnalités de composants logiciels de synthèse d'images enfouissables en partie dans la carte graphique pour permettre la parallélisation des traitements cellulaires

Staphylococcus aureus infective endocarditis versus bacteremia strains: Subtle genetic differences at stake

AbstractInfective endocarditis (IE)(1) is a severe condition complicating 10–25% of Staphylococcus aureus bacteremia. Although host-related IE risk factors have been identified, the involvement of bacterial features in IE complication is still unclear. We characterized strictly defined IE and bacteremia isolates and searched for discriminant features. S. aureus isolates causing community-acquired, definite native-valve IE (n=72) and bacteremia (n=54) were collected prospectively as part of a French multicenter cohort. Phenotypic traits previously reported or hypothesized to be involved in staphylococcal IE pathogenesis were tested. In parallel, the genotypic profiles of all isolates, obtained by microarray, were analyzed by discriminant analysis of principal components (DAPC)(2). No significant difference was observed between IE and bacteremia strains, regarding either phenotypic or genotypic univariate analyses. However, the multivariate statistical tool DAPC, applied on microarray data, segregated IE and bacteremia isolates: IE isolates were correctly reassigned as such in 80.6% of the cases (C-statistic 0.83, P<0.001). The performance of this model was confirmed with an independent French collection IE and bacteremia isolates (78.8% reassignment, C-statistic 0.65, P<0.01). Finally, a simple linear discriminant function based on a subset of 8 genetic markers retained valuable performance both in study collection (86.1%, P<0.001) and in the independent validation collection (81.8%, P<0.01). We here show that community-acquired IE and bacteremia S. aureus isolates are genetically distinct based on subtle combinations of genetic markers. This finding provides the proof of concept that bacterial characteristics may contribute to the occurrence of IE in patients with S. aureus bacteremia

Meta-analysis of SHANK Mutations in Autism Spectrum Disorders: A Gradient of Severity in Cognitive Impairments.

International audienceSHANK genes code for scaffold proteins located at the post-synaptic density of glutamatergic synapses. In neurons, SHANK2 and SHANK3 have a positive effect on the induction and maturation of dendritic spines, whereas SHANK1 induces the enlargement of spine heads. Mutations in SHANK genes have been associated with autism spectrum disorders (ASD), but their prevalence and clinical relevance remain to be determined. Here, we performed a new screen and a meta-analysis of SHANK copy-number and coding-sequence variants in ASD. Copy-number variants were analyzed in 5,657 patients and 19,163 controls, coding-sequence variants were ascertained in 760 to 2,147 patients and 492 to 1,090 controls (depending on the gene), and, individuals carrying de novo or truncating SHANK mutations underwent an extensive clinical investigation. Copy-number variants and truncating mutations in SHANK genes were present in ∼1% of patients with ASD: mutations in SHANK1 were rare (0.04%) and present in males with normal IQ and autism; mutations in SHANK2 were present in 0.17% of patients with ASD and mild intellectual disability; mutations in SHANK3 were present in 0.69% of patients with ASD and up to 2.12% of the cases with moderate to profound intellectual disability. In summary, mutations of the SHANK genes were detected in the whole spectrum of autism with a gradient of severity in cognitive impairment. Given the rare frequency of SHANK1 and SHANK2 deleterious mutations, the clinical relevance of these genes remains to be ascertained. In contrast, the frequency and the penetrance of SHANK3 mutations in individuals with ASD and intellectual disability-more than 1 in 50-warrant its consideration for mutation screening in clinical practice

Architectural model of a biological retina using cellular automata

International audienceDevelopments in neurophysiology focusing on foveal vision have characterized more and more precisely the spatiotemporal processing that is well adapted to the regularization of the visual information within the retina. The works described in this article focus on a simplified architec-tural model based on features and mechanisms of adaptation in the retina. Similarly to the bio-logical retina, which transforms luminance information into a series of encoded representations of image characteristics transmitted to the brain, our structural model allows us to reveal more information in the scene. Our modeling of the different functional pathways permits the mapping of important complementary information types at abstract levels of image analysis, and thereby allows a better exploitation of visual clues. Our model is based on a distributed cellular automata network and simulates the retinal processing of stimuli that are stationary or in motion. Thanks to its capacity for dynamic adaptation, our model can adapt itself to different scenes (e.g., bright and dim, stationary and moving, etc.) and can parallelize those processing steps that can be supported by parallel calculators

A model of biological retina architecture based on cellular automata and morphological filters

La vision biologique des mammifères présente des performances globales dont nous nous sommes inspirés pour l'extraction de caractéristiques dans les images naturelles en vue de la reconnaissance de formes. La modélisation de l'architecture des premières couches de la rétine biologique couplée au concept d'automate cellulaire ouvre des perspectives nouvelles dans le développement d'outils adaptatifs pour la vision par ordinateur. Le traitement cellulaire est réalisé par des opérateurs simples morphologiques dans l'objectif de permettre une implémentation temps réel

Retina Simulation using Cellular Automata and GPU Programming

11 pagesInternational audienceThis article shows how the architectural modelization of biological retina allows real-time performances, on standard widespread computing systems. First, we describe the biological retina with regard to its pipeline architecture, detailing its layer behaviours and properties. Then we propose a corresponding pipelined model of artificial retina based on cellular automata. In this work, the main innovation is the computing method based on the programming of a personal computer graphical card using OpenGL shading language. The last section demonstrates the efficiency of our model through numerical and graphical results. We lay particular emphasis on the fact that our direct implementation of the Graphical Processor Unit (GPU) provides computation power about 20 times as fast as conventional programming

Système de mesure et d’information d’un bâtiment dédié à la rénovation thermique de ses studios

Présentation effectuée le 09/09International audienceCet article présente une démarche de recherche de stratégies d'actions sur le plan énergétique pour assurer la rénovation thermique d'un bâtiment en phase d'exploitation. En évaluant les performances du bâti dans son environnement, nous pourrons déterminer et phaser les actions à mener. Pour cette évaluation, nous proposons une approche systémique qui consiste à décomposer un bâtiment en sous-systèmes qui échangent de l'énergie. Pour mieux comprendre ces échanges d'énergie, il est nécessaire de maîtriser les ordres de grandeur des différents apports et consommations. Nous avons ainsi équipé un bâtiment existant d'une instrumentation peu intrusive, géolocalisée, en modifiant a minima les installations existantes. Des modèles multiphysiques de comportement thermique et les simulations associées, sont un préalable pour tester et valider des stratégies