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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Bertrand Neron; Remi Denise; Charles Coluzzi; Marie Touchon; +2 Authors

    Complex cellular functions are usually encoded by a set of genes in one or a few organized genetic loci in microbial genomes. Macromolecular System Finder (MacSyFinder) is a program that uses these properties to model and then annotate cellular functions in microbial genomes. This is done by integrating the identification of each individual gene at the level of the molecular system. We hereby present a major release of MacSyFinder (version 2) coded in Python 3. The code was improved and rationalized to facilitate future maintainability. Several new features were added to allow more flexible modelling of the systems. We introduce a more intuitive and comprehensive search engine to identify all the best candidate systems and sub-optimal ones that respect the models' constraints. We also introduce the novel macsydata companion tool that enables the easy installation and broad distribution of the models developed for MacSyFinder (macsy-models) from GitHub repositories. Finally, we have updated and improved MacSyFinder popular models: TXSScan to identify protein secretion systems, TFFscan to identify type IV filaments, CONJscan to identify conjugative systems, and CasFinder to identify CRISPR associated proteins. MacSyFinder and the updated models are available at: https://github.com/gem-pasteur/macsyfinder and https://github.com/macsy-models.

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    Peer Community Journal
    Article . 2023 . Peer-reviewed
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    DOAJ
    Article . 2023
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    https://doi.org/10.1101/2022.0...
    Preprint . 2022 . Peer-reviewed
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      https://doi.org/10.1101/2022.0...
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  • Authors: Bardiaux, Benjamin;

    ARIAweb is a a server for that implements the ARIA software (Ambiguous Restraints for Iterative Assignment) for automated NMR structure calculation with enhanced analysis and visualization.

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    Authors: Allain, Fabrice; Mareuil, Fabien; Ménager, Hervé; Nilges, Michael; +1 Authors

    Abstract Nuclear magnetic resonance (NMR) spectroscopy is a method of choice to study the dynamics and determine the atomic structure of macromolecules in solution. The standalone program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and structure calculation is well established in the NMR community. To ultimately provide a perfectly transparent and easy to use service, we designed an online user interface to ARIA with additional functionalities. Data conversion, structure calculation setup and execution, followed by interactive visualization of the generated 3D structures are all integrated in ARIAweb and freely accessible at https://ariaweb.pasteur.fr.

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    Nucleic Acids Research
    Article
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    Nucleic Acids Research
    Article . 2020 . Peer-reviewed
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    Authors: Hanna Julienne; Pierre Lechat; Vincent Guillemot; Carla Lasry; +6 Authors

    AbstractGenome-wide association study (GWAS) has been the driving force for identifying association between genetic variants and human phenotypes. Thousands of GWAS summary statistics covering a broad range of human traits and diseases are now publicly available. These GWAS have proven their utility for a range of secondary analyses, including in particular the joint analysis of multiple phenotypes to identify new associated genetic variants. However, although several methods have been proposed, there are very few large-scale applications published so far because of challenges in implementing these methods on real data. Here, we present JASS (Joint Analysis of Summary Statistics), a polyvalent Python package that addresses this need. Our package incorporates recently developed joint tests such as the omnibus approach and various weighted sum of Z-score tests while solving all practical and computational barriers for large-scale multivariate analysis of GWAS summary statistics. This includes data cleaning and harmonization tools, an efficient algorithm for fast derivation of joint statistics, an optimized data management process and a web interface for exploration purposes. Both benchmark analyses and real data applications demonstrated the robustness and strong potential of JASS for the detection of new associated genetic variants. Our package is freely available at https://gitlab.pasteur.fr/statistical-genetics/jass.

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    NAR Genomics and Bioinformatics
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    NAR Genomics and Bioinformatics
    Article . 2020 . Peer-reviewed
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      NAR Genomics and Bioinformatics
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      NAR Genomics and Bioinformatics
      Article . 2020 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Aschard, Hugues; Julienne, Hanna; Guillemot, Vincent; Lechat, Pierre; +2 Authors

    software package that handles the computation of the joint statistics over sets of selected GWAS results, and the interactive exploration of the results through a web interface.

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    bio.tools
    Software . 2020
    License: MIT
    Data sources: bio.tools
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      bio.tools
      Software . 2020
      License: MIT
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    Authors: Zhukova, Anna; Gascuel, Olivier;

    Fast inference and visualization of ancestral scenarios. PastML infers ancestral characters on a rooted phylogenetic tree with annotated tips, using maximum likelihood or parsimony. The result is then visualised as a zoomable html map.

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    bio.tools
    Software . 2019
    License: GPL-3.0
    Data sources: bio.tools
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      bio.tools
      Software . 2019
      License: GPL-3.0
      Data sources: bio.tools
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    Authors: Sohta A. Ishikawa; Anna Zhukova; Wataru Iwasaki; Olivier Gascuel;

    AbstractThe reconstruction of ancestral scenarios is widely used to study the evolution of characters along phylogenetic trees. One commonly uses the marginal posterior probabilities of the character states, or the joint reconstruction of the most likely scenario. However, marginal reconstructions provide users with state probabilities, which are difficult to interpret and visualize, whereas joint reconstructions select a unique state for every tree node and thus do not reflect the uncertainty of inferences.We propose a simple and fast approach, which is in between these two extremes. We use decision-theory concepts (namely, the Brier score) to associate each node in the tree to a set of likely states. A unique state is predicted in tree regions with low uncertainty, whereas several states are predicted in uncertain regions, typically around the tree root. To visualize the results, we cluster the neighboring nodes associated with the same states and use graph visualization tools. The method is implemented in the PastML program and web server.The results on simulated data demonstrate the accuracy and robustness of the approach. PastML was applied to the phylogeography of Dengue serotype 2 (DENV2), and the evolution of drug resistances in a large HIV data set. These analyses took a few minutes and provided convincing results. PastML retrieved the main transmission routes of human DENV2 and showed the uncertainty of the human-sylvatic DENV2 geographic origin. With HIV, the results show that resistance mutations mostly emerge independently under treatment pressure, but resistance clusters are found, corresponding to transmissions among untreated patients.

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    Molecular Biology and Evolution
    Article . 2019 . Peer-reviewed
    License: CC BY NC
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    Molecular Biology and Evolution
    Article . Preprint
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    Authors: Néron, Bertrand; Néron, Bertrand; Abby, Sophie;

    Program to model and detect macromolecular systems, genetic pathways... in protein datasets. In prokaryotes, these systems have often evolutionarily conserved properties: they are made of conserved components, and are encoded in compact loci (conserved genetic architecture). The user models these systems to reflect these conserved features, and to allow their efficient detection.

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    bio.tools
    Software . 2016
    License: GPL-3.0
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      bio.tools
      Software . 2016
      License: GPL-3.0
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Bertrand Neron; Remi Denise; Charles Coluzzi; Marie Touchon; +2 Authors

    Complex cellular functions are usually encoded by a set of genes in one or a few organized genetic loci in microbial genomes. Macromolecular System Finder (MacSyFinder) is a program that uses these properties to model and then annotate cellular functions in microbial genomes. This is done by integrating the identification of each individual gene at the level of the molecular system. We hereby present a major release of MacSyFinder (version 2) coded in Python 3. The code was improved and rationalized to facilitate future maintainability. Several new features were added to allow more flexible modelling of the systems. We introduce a more intuitive and comprehensive search engine to identify all the best candidate systems and sub-optimal ones that respect the models' constraints. We also introduce the novel macsydata companion tool that enables the easy installation and broad distribution of the models developed for MacSyFinder (macsy-models) from GitHub repositories. Finally, we have updated and improved MacSyFinder popular models: TXSScan to identify protein secretion systems, TFFscan to identify type IV filaments, CONJscan to identify conjugative systems, and CasFinder to identify CRISPR associated proteins. MacSyFinder and the updated models are available at: https://github.com/gem-pasteur/macsyfinder and https://github.com/macsy-models.

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  • Authors: Bardiaux, Benjamin;

    ARIAweb is a a server for that implements the ARIA software (Ambiguous Restraints for Iterative Assignment) for automated NMR structure calculation with enhanced analysis and visualization.

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    Authors: Allain, Fabrice; Mareuil, Fabien; Ménager, Hervé; Nilges, Michael; +1 Authors

    Abstract Nuclear magnetic resonance (NMR) spectroscopy is a method of choice to study the dynamics and determine the atomic structure of macromolecules in solution. The standalone program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and structure calculation is well established in the NMR community. To ultimately provide a perfectly transparent and easy to use service, we designed an online user interface to ARIA with additional functionalities. Data conversion, structure calculation setup and execution, followed by interactive visualization of the generated 3D structures are all integrated in ARIAweb and freely accessible at https://ariaweb.pasteur.fr.

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    Nucleic Acids Research
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    Nucleic Acids Research
    Article . 2020 . Peer-reviewed
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    Authors: Hanna Julienne; Pierre Lechat; Vincent Guillemot; Carla Lasry; +6 Authors

    AbstractGenome-wide association study (GWAS) has been the driving force for identifying association between genetic variants and human phenotypes. Thousands of GWAS summary statistics covering a broad range of human traits and diseases are now publicly available. These GWAS have proven their utility for a range of secondary analyses, including in particular the joint analysis of multiple phenotypes to identify new associated genetic variants. However, although several methods have been proposed, there are very few large-scale applications published so far because of challenges in implementing these methods on real data. Here, we present JASS (Joint Analysis of Summary Statistics), a polyvalent Python package that addresses this need. Our package incorporates recently developed joint tests such as the omnibus approach and various weighted sum of Z-score tests while solving all practical and computational barriers for large-scale multivariate analysis of GWAS summary statistics. This includes data cleaning and harmonization tools, an efficient algorithm for fast derivation of joint statistics, an optimized data management process and a web interface for exploration purposes. Both benchmark analyses and real data applications demonstrated the robustness and strong potential of JASS for the detection of new associated genetic variants. Our package is freely available at https://gitlab.pasteur.fr/statistical-genetics/jass.

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    NAR Genomics and Bioinformatics
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    Authors: Aschard, Hugues; Julienne, Hanna; Guillemot, Vincent; Lechat, Pierre; +2 Authors

    software package that handles the computation of the joint statistics over sets of selected GWAS results, and the interactive exploration of the results through a web interface.

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    bio.tools
    Software . 2020
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      bio.tools
      Software . 2020
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    Authors: Zhukova, Anna; Gascuel, Olivier;

    Fast inference and visualization of ancestral scenarios. PastML infers ancestral characters on a rooted phylogenetic tree with annotated tips, using maximum likelihood or parsimony. The result is then visualised as a zoomable html map.

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    bio.tools
    Software . 2019
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      bio.tools
      Software . 2019
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    Authors: Sohta A. Ishikawa; Anna Zhukova; Wataru Iwasaki; Olivier Gascuel;

    AbstractThe reconstruction of ancestral scenarios is widely used to study the evolution of characters along phylogenetic trees. One commonly uses the marginal posterior probabilities of the character states, or the joint reconstruction of the most likely scenario. However, marginal reconstructions provide users with state probabilities, which are difficult to interpret and visualize, whereas joint reconstructions select a unique state for every tree node and thus do not reflect the uncertainty of inferences.We propose a simple and fast approach, which is in between these two extremes. We use decision-theory concepts (namely, the Brier score) to associate each node in the tree to a set of likely states. A unique state is predicted in tree regions with low uncertainty, whereas several states are predicted in uncertain regions, typically around the tree root. To visualize the results, we cluster the neighboring nodes associated with the same states and use graph visualization tools. The method is implemented in the PastML program and web server.The results on simulated data demonstrate the accuracy and robustness of the approach. PastML was applied to the phylogeography of Dengue serotype 2 (DENV2), and the evolution of drug resistances in a large HIV data set. These analyses took a few minutes and provided convincing results. PastML retrieved the main transmission routes of human DENV2 and showed the uncertainty of the human-sylvatic DENV2 geographic origin. With HIV, the results show that resistance mutations mostly emerge independently under treatment pressure, but resistance clusters are found, corresponding to transmissions among untreated patients.

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    Molecular Biology and Evolution
    Article . 2019 . Peer-reviewed
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    Molecular Biology and Evolution
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    Authors: Néron, Bertrand; Néron, Bertrand; Abby, Sophie;

    Program to model and detect macromolecular systems, genetic pathways... in protein datasets. In prokaryotes, these systems have often evolutionarily conserved properties: they are made of conserved components, and are encoded in compact loci (conserved genetic architecture). The user models these systems to reflect these conserved features, and to allow their efficient detection.

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