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4. The Galaxy platform for accessible, reproducible, and collaborative data analyses: 2024 update

Author

Abueg, L.A.L., Afgan, E., Allart, O., Awan, A.H., Bacon, W.A., Baker, D., Bassetti, M., Batut, B., Bernt, Matthias, Blankenberg, D., Bombarely, A., Bretaudeau, A., Bromhead, C.J., Burke, M.L., Capon, P.K., Čech, M., Chavero-Díez, M., Chilton, J.M., Collins, T.J., Coppens, F., Coraor, N., Cuccuru, G., Cumbo, F., Davis, J., De Geest, P.F., de Koning, W., Demko, M., DeSanto, A., Domínguez Begines, J.M., Doyle, M.A., Droesbeke, B., Erxleben-Eggenhofer, A., Föll, M.C., Formenti, G., Fouilloux, A., Gangazhe, R., Genthon, T., Goecks, J., Gonzalez Beltran, A.N., Goonasekera, N.A., Goué, N., Griffin, T.J., Grüning, B.A., Guerler, A., Gundersen, S., Gustafsson, O.J.R., Hall, C., Harrop, T.W., Hecht, H., Heidari, A., Heisner, T., Heyl, F., Hiltemann, S., Hotz, H.-R., Hyde, C.J., Jagtap, P.D., Jakiela, J., Johnson, J.E., Joshi, J., Jossé, M., Jum’ah, K., Kalaš, M., Kamieniecka, K., Kayikcioglu, T., Konkol, M., Kostrykin, L., Kucher, N., Kumar, A., Kuntz, M., Lariviere, D., Lazarus, R., Le Bras, Y., Le Corguillé, G., Lee, J., Leo, S., Liborio, L., Libouban, R., López Tabernero, D., Lopez-Delisle, L., Los, L.S., Mahmoud, A., Makunin, I., Marin, P., Mehta, S., Mok, W., Moreno, P.A., Morier-Genoud, F., Mosher, S., Müller, T., Nasr, E., Nekrutenko, A., Nelson T.M., Oba, A.J., Ostrovsky, A., Polunina, P.V., Poterlowicz, K., Price, E.J., Price, G.R., Rasche, H., Raubenolt, B., Abueg, L.A.L., Afgan, E., Allart, O., Awan, A.H., Bacon, W.A., Baker, D., Bassetti, M., Batut, B., Bernt, Matthias, Blankenberg, D., Bombarely, A., Bretaudeau, A., Bromhead, C.J., Burke, M.L., Capon, P.K., Čech, M., Chavero-Díez, M., Chilton, J.M., Collins, T.J., Coppens, F., Coraor, N., Cuccuru, G., Cumbo, F., Davis, J., De Geest, P.F., de Koning, W., Demko, M., DeSanto, A., Domínguez Begines, J.M., Doyle, M.A., Droesbeke, B., Erxleben-Eggenhofer, A., Föll, M.C., Formenti, G., Fouilloux, A., Gangazhe, R., Genthon, T., Goecks, J., Gonzalez Beltran, A.N., Goonasekera, N.A., Goué, N., Griffin, T.J., Grüning, B.A., Guerler, A., Gundersen, S., Gustafsson, O.J.R., Hall, C., Harrop, T.W., Hecht, H., Heidari, A., Heisner, T., Heyl, F., Hiltemann, S., Hotz, H.-R., Hyde, C.J., Jagtap, P.D., Jakiela, J., Johnson, J.E., Joshi, J., Jossé, M., Jum’ah, K., Kalaš, M., Kamieniecka, K., Kayikcioglu, T., Konkol, M., Kostrykin, L., Kucher, N., Kumar, A., Kuntz, M., Lariviere, D., Lazarus, R., Le Bras, Y., Le Corguillé, G., Lee, J., Leo, S., Liborio, L., Libouban, R., López Tabernero, D., Lopez-Delisle, L., Los, L.S., Mahmoud, A., Makunin, I., Marin, P., Mehta, S., Mok, W., Moreno, P.A., Morier-Genoud, F., Mosher, S., Müller, T., Nasr, E., Nekrutenko, A., Nelson T.M., Oba, A.J., Ostrovsky, A., Polunina, P.V., Poterlowicz, K., Price, E.J., Price, G.R., Rasche, H., and Raubenolt, B.

Abstract

Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.

Published
2024

32. Résultats et efficacité du traitement endovasculaire des occlusions veineuses chroniques proximales : une étude multicentrique nationale de la Société française d’imagerie cardio-vasculaire

Author

Douane, F., primary, David, Arthur, additional, Thony, F., additional, Sapoval, M., additional, Del Giudice, C., additional, Goyault, G., additional, Loffroy, R., additional, Le Bras, Y., additional, Monnin, V., additional, Heautot, J.-F., additional, Rousseau, H., additional, Martinelli, T., additional, Thouveny, F., additional, Barral, P.-A., additional, Le Pennec, V., additional, Chabrot, P., additional, Rogopoulos, A., additional, Rodière, M., additional, and Espitia, O., additional

Published
2021
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40. RNA profiling of human testicular cells identifies syntenic lncRNAs associated with spermatogenesis

Author

Rolland, Antoine D., Evrard, B, Darde, T A, Le Béguec, C, Le Bras, Y, Bensalah, K, Lavoué, S, Jost, B, Primig, M, Dejucq-Rainsford, Nathalie, Chalmel, F, Jégou, Bernard, Institut de recherche en santé, environnement et travail (Irset), Université d'Angers (UA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), École des Hautes Études en Santé Publique [EHESP] (EHESP), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), CHU Pontchaillou [Rennes], Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), EHESP-Irset (EHESP-Irset), Rennes Métropole ‘Défis Scientifiques Émergents’, N 10028NN, INERIS-STORM, l’Ecole des Hautes Études en Santé Publique, l’Université de Rennes 1, and l’Institut National de la Santé et de la Recherche Médicale

Subjects
[SDV]Life Sciences [q-bio], Novel unannotated transcripts, Human spermatogenesis, Long non-coding RNAs, RNA profiling, Synteny, Expression conservation
Abstract

International audience; STUDY QUESTIONIs the noncoding transcriptional landscape during spermatogenesis conserved between human and rodents?SUMMARY ANSWERWe identified a core group of 113 long noncoding RNAs (lncRNAs) and 20 novel genes dynamically and syntenically transcribed during spermatogenesis.WHAT IS KNOWN ALREADYSpermatogenesis is a complex differentiation process driven by a tightly regulated and highly specific gene expression program. Recently, several studies in various species have established that a large proportion of known lncRNAs are preferentially expressed during meiosis and spermiogenesis in a testis-specific manner.STUDY DESIGN, SIZE, DURATIONTo further investigate lncRNA expression in human spermatogenesis, we carried out a cross-species RNA profiling study using isolated testicular cells.PARTICIPANTS/MATERIALS, SETTING, METHODSHuman testes were obtained from post-mortem donors (N = 8, 51 years old on average) or from prostate cancer patients with no hormonal treatment (N = 9, 80 years old on average) and only patients with full spermatogenesis were used to prepare enriched populations of spermatocytes, spermatids, Leydig cells, peritubular cells and Sertoli cells. To minimize potential biases linked to inter-patient variations, RNAs from two or three donors were pooled prior to RNA-sequencing (paired-end, strand-specific). Resulting reads were mapped to the human genome, allowing for assembly and quantification of corresponding transcripts.MAIN RESULTS AND THE ROLE OF CHANCEOur RNA-sequencing analysis of pools of isolated human testicular cells enabled us to reconstruct over 25 000 transcripts. Among them we identified thousands of lncRNAs, as well as many previously unidentified genes (novel unannotated transcripts) that share many properties of lncRNAs. Of note is that although noncoding genes showed much lower synteny than protein-coding ones, a significant fraction of syntenic lncRNAs displayed conserved expression during spermatogenesis.LARGE SCALE DATARaw data files (fastq) and a searchable table (.xlss) containing information on genomic features and expression data for all refined transcripts have been submitted to the NCBI Gene Expression Omnibus under accession number GSE74896.LIMITATIONS, REASONS FOR CAUTIONIsolation procedures may alter the physiological state of testicular cells, especially for somatic cells, leading to substantial changes at the transcriptome level. We therefore cross-validated our findings with three previously published transcriptomic analyses of human spermatogenesis. Despite the use of stringent filtration criteria, i.e. expression cut-off of at least three fragments per kilobase of exon model per million reads mapped, fold-change of at least three and false discovery rate adjusted P-values of less than

Published
2019
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