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Your search keyword '"Larmande, Pierre"' showing total 7 results
Start Over Author "Larmande, Pierre" Journal gigascience
7 results on '"Larmande, Pierre"'

1. RicePilaf: a post-GWAS/QTL dashboard to integrate pangenomic, coexpression, regulatory, epigenomic, ontology, pathway, and text-mining information to provide functional insights into rice QTLs and GWAS loci

Author

Shrestha, Anish M S, primary, Gonzales, Mark Edward M, additional, Ong, Phoebe Clare L, additional, Larmande, Pierre, additional, Lee, Hyun-Sook, additional, Jeung, Ji-Ung, additional, Kohli, Ajay, additional, Chebotarov, Dmytro, additional, Mauleon, Ramil P, additional, Lee, Jae-Sung, additional, and McNally, Kenneth L, additional

Published
2024
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2. Gigwa v2—Extended and improved genotype investigator

Author

Sempéré, Guilhem, Pétel, Adrien, Rouard, Mathieu, Frouin, Julien, Hueber, Yann, De Bellis, Fabien, Larmande, Pierre, Interactions hôtes-vecteurs-parasites-environnement dans les maladies tropicales négligées dues aux trypanosomatides (UMR INTERTRYP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université de Bordeaux (UB), Institut National de la Recherche Agronomique (INRA), Université de Montpellier (UM), CGIAR, Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), French National Research Agency (ANR) : ANR-16-IDEX-0006, and ANR-16-IDEX-0006,MUSE,MUSE(2016)

Subjects
Genotype, SNP, interoperability, Logiciel, Polymorphism, Single Nucleotide, web, F30 - Génétique et amélioration des plantes, génomique, HapMap, User-Computer Interface, Variation génétique, MongoDB, Databases, Genetic, Technical Note, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, PLINK, Humans, Traitement des données, Internet, Vegetal Biology, genomic variations, VCF, NoSQL, indel, REST, BrAPI, GA4GH, Computational Biology, Genetic Variation, High-Throughput Nucleotide Sequencing, Genomics, L10 - Génétique et amélioration des animaux, interopérabilité, U30 - Méthodes de recherche, Biologie végétale, Génotype, Software
Abstract

International audience; Background: The study of genetic variations is the basis of many research domains in biology. From genome structure to population dynamics, many applications involve the use of genetic variants. The advent of next-generation sequencing technologies led to such a flood of data that the daily work of scientists is often more focused on data management than data analysis. This mass of genotyping data poses several computational challenges in terms of storage, search, sharing, analysis, and visualization. While existing tools try to solve these challenges, few of them offer a comprehensive and scalable solution. Results: Gigwa v2 is an easy-to-use, species-agnostic web application for managing and exploring high-density genotyping data. It can handle multiple databases and may be installed on a local computer or deployed as an online data portal. It supports various standard import and export formats, provides advanced filtering options, and offers means to visualize density charts or push selected data into various stand-alone or online tools. It implements 2 standard RESTful application programming interfaces, GA4GH, which is health-oriented, and BrAPI, which is breeding-oriented, thus offering wide possibilities of interaction with third-party applications. The project home page provides a list of live instances allowing users to test the system on public data (or reasonably sized user-provided data). Conclusions: This new version of Gigwa provides a more intuitive and more powerful way to explore large amounts of genotyping data by offering a scalable solution to search for genotype patterns, functional annotations, or more complex filtering. Furthermore, its user-friendliness and interoperability make it widely accessible to the life science community.

Published
2019
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3. Corrigendum to: Rice Galaxy: an open resource for plant science

Author

Juanillas, Venice, primary, Dereeper, Alexis, additional, Beaume, Nicolas, additional, Droc, Gaetan, additional, Dizon, Joshua, additional, Mendoza, John Robert, additional, Perdon, Jon Peter, additional, Mansueto, Locedie, additional, Triplett, Lindsay, additional, Lang, Jillian, additional, Zhou, Gabriel, additional, Ratharanjan, Kunalan, additional, Plale, Beth, additional, Haga, Jason, additional, Leach, Jan E, additional, Ruiz, Manuel, additional, Thomson, Michael, additional, Alexandrov, Nickolai, additional, Larmande, Pierre, additional, Kretzschmar, Tobias, additional, and Mauleon, Ramil P, additional

Published
2019
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4. Rice Galaxy: an open resource for plant science

Author

Juanillas, Venice, primary, Dereeper, Alexis, additional, Beaume, Nicolas, additional, Droc, Gaetan, additional, Dizon, Joshua, additional, Mendoza, John Robert, additional, Perdon, Jon Peter, additional, Mansueto, Locedie, additional, Triplett, Lindsay, additional, Lang, Jillian, additional, Zhou, Gabriel, additional, Ratharanjan, Kunalan, additional, Plale, Beth, additional, Haga, Jason, additional, Leach, Jan E, additional, Ruiz, Manuel, additional, Thomson, Michael, additional, Alexandrov, Nickolai, additional, Larmande, Pierre, additional, Kretzschmar, Tobias, additional, and Mauleon, Ramil P, additional

Published
2019
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7. Gigwa-Genotype investigator for genomewide analyses.

Author

Sempéré, Guilhem, Philippe, Florian, Dereeper, Alexis, Ruiz, Manuel, Sarah, Gautier, and Larmande, Pierre

Subjects
GENOTYPES, INFORMATION retrieval, NUCLEOTIDE sequence
Abstract

Background: Exploring the structure of genomes and analyzing their evolution is essential to understanding the ecological adaptation of organisms. However, with the large amounts of data being produced by next-generation sequencing, computational challenges arise in terms of storage, search, sharing, analysis and visualization. This is particularly true with regards to studies of genomic variation, which are currently lacking scalable and user-friendly data exploration solutions. Description: Here we present Gigwa, a web-based tool that provides an easy and intuitive way to explore large amounts of genotyping data by filtering it not only on the basis of variant features, including functional annotations, but also on genotype patterns. The data storage relies on MongoDB, which offers good scalability properties. Gigwa can handle multiple databases and may be deployed in either single- or multi-user mode. In addition, it provides a wide range of popular export formats. Conclusions: The Gigwa application is suitable for managing large amounts of genomic variation data. Its user-friendly web interface makes such processing widely accessible. It can either be simply deployed on a workstation or be used to provide a shared data portal for a given community of researchers. [ABSTRACT FROM AUTHOR]

Published
2016
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