30 research outputs found

    An Integration-Oriented Ontology to Govern Evolution in Big Data Ecosystems

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    Big Data architectures allow to flexibly store and process heterogeneous data, from multiple sources, in their original format. The structure of those data, commonly supplied by means of REST APIs, is continuously evolving. Thus data analysts need to adapt their analytical processes after each API release. This gets more challenging when performing an integrated or historical analysis. To cope with such complexity, in this paper, we present the Big Data Integration ontology, the core construct to govern the data integration process under schema evolution by systematically annotating it with information regarding the schema of the sources. We present a query rewriting algorithm that, using the annotated ontology, converts queries posed over the ontology to queries over the sources. To cope with syntactic evolution in the sources, we present an algorithm that semi-automatically adapts the ontology upon new releases. This guarantees ontology-mediated queries to correctly retrieve data from the most recent schema version as well as correctness in historical queries. A functional and performance evaluation on real-world APIs is performed to validate our approach.Comment: Preprint submitted to Information Systems. 35 page

    High-throughput sequencing contribution in bioinformatics analysis of hepatitis C virus genome

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    Le sĂ©quençage haut dĂ©bit a Ă©tĂ© utilisĂ© dans ce travail pour reconstruire avec des mĂ©thodes adaptĂ©es le gĂ©nomeviral entier du virus de l’hĂ©patite C (VHC) notamment pour le typer avec prĂ©cision. Une Ă©tude a ainsi permisde mettre en Ă©vidence la prĂ©sence d’une forme recombinante du VHC chez un patient. Une autre a permisde typer et dĂ©tecter les mutations de rĂ©sistance de plusieurs souches de VHC de gĂ©notypes diffĂ©rents. Enfin,une derniĂšre Ă©tude basĂ©e sur cette approche a permis de dĂ©couvrir une souche VHC appartenant Ă  un nouveausous-type. Le sĂ©quençage haut dĂ©bit a aussi Ă©tĂ© utilisĂ© dans ce travail pour dĂ©tecter des infections multiples etanalyser l’évolution virale en ciblant des gĂšnes du VHC et en mettant en Ɠuvre des mĂ©thodes non spĂ©cifiquespour 2 patients VHC sous traitement. Cette Ă©tude rĂ©trospective a permis de dĂ©finir la composition de chaqueĂ©chantillon temporel, estimer leur diversitĂ© nuclĂ©otidique, explorer la structure gĂ©nĂ©tique de la population viraleet son Ă©volution temporelle et dater les infections secondaires. Les rĂ©sultats obtenus supportent l’hypothĂšse d’unmĂ©canisme d’apparition de rĂ©sistance au traitement (selective sweeps).High-throughput sequencing has been used in this work to reconstruct with adapted methods the whole genomeof the hepatitis C virus (HCV) particularly for accurately typing the virus. Thus, we managed to detect in a studya recombinant form of HCV circulating within a patient. We typed and detected in another study resistancemutations of several HCV strains of different genotypes. Finally, a last study based on this approach enabled touncover a HCV strain belonging to a new subtype. High-throughput sequencing has also been used in this workto detect multiple infections and analyze viral evolution with targeted HCV genes and non-specific methods for2 HCV patients under treatment. This retrospective study enabled to define the composition of each temporalsample, assess their nucleotide diversity, investigate viral population genetic structure and temporal evolutionand date secondary infections. Results of this analysis support the hypothesis of onset mechanism of treatmentresistance (selective sweeps)

    Apport du séquençage haut débit dans l'analyse bioinformatique du génome du virus de l'hépatite C

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    High-throughput sequencing has been used in this work to reconstruct with adapted methods the whole genomeof the hepatitis C virus (HCV) particularly for accurately typing the virus. Thus, we managed to detect in a studya recombinant form of HCV circulating within a patient. We typed and detected in another study resistancemutations of several HCV strains of different genotypes. Finally, a last study based on this approach enabled touncover a HCV strain belonging to a new subtype. High-throughput sequencing has also been used in this workto detect multiple infections and analyze viral evolution with targeted HCV genes and non-specific methods for2 HCV patients under treatment. This retrospective study enabled to define the composition of each temporalsample, assess their nucleotide diversity, investigate viral population genetic structure and temporal evolutionand date secondary infections. Results of this analysis support the hypothesis of onset mechanism of treatmentresistance (selective sweeps).Le sĂ©quençage haut dĂ©bit a Ă©tĂ© utilisĂ© dans ce travail pour reconstruire avec des mĂ©thodes adaptĂ©es le gĂ©nomeviral entier du virus de l’hĂ©patite C (VHC) notamment pour le typer avec prĂ©cision. Une Ă©tude a ainsi permisde mettre en Ă©vidence la prĂ©sence d’une forme recombinante du VHC chez un patient. Une autre a permisde typer et dĂ©tecter les mutations de rĂ©sistance de plusieurs souches de VHC de gĂ©notypes diffĂ©rents. Enfin,une derniĂšre Ă©tude basĂ©e sur cette approche a permis de dĂ©couvrir une souche VHC appartenant Ă  un nouveausous-type. Le sĂ©quençage haut dĂ©bit a aussi Ă©tĂ© utilisĂ© dans ce travail pour dĂ©tecter des infections multiples etanalyser l’évolution virale en ciblant des gĂšnes du VHC et en mettant en Ɠuvre des mĂ©thodes non spĂ©cifiquespour 2 patients VHC sous traitement. Cette Ă©tude rĂ©trospective a permis de dĂ©finir la composition de chaqueĂ©chantillon temporel, estimer leur diversitĂ© nuclĂ©otidique, explorer la structure gĂ©nĂ©tique de la population viraleet son Ă©volution temporelle et dater les infections secondaires. Les rĂ©sultats obtenus supportent l’hypothĂšse d’unmĂ©canisme d’apparition de rĂ©sistance au traitement (selective sweeps)

    Apport du séquençage haut débit dans l'analyse bioinformatique du génome du virus de l'hépatite C

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    High-throughput sequencing has been used in this work to reconstruct with adapted methods the whole genomeof the hepatitis C virus (HCV) particularly for accurately typing the virus. Thus, we managed to detect in a studya recombinant form of HCV circulating within a patient. We typed and detected in another study resistancemutations of several HCV strains of different genotypes. Finally, a last study based on this approach enabled touncover a HCV strain belonging to a new subtype. High-throughput sequencing has also been used in this workto detect multiple infections and analyze viral evolution with targeted HCV genes and non-specific methods for2 HCV patients under treatment. This retrospective study enabled to define the composition of each temporalsample, assess their nucleotide diversity, investigate viral population genetic structure and temporal evolutionand date secondary infections. Results of this analysis support the hypothesis of onset mechanism of treatmentresistance (selective sweeps).Le sĂ©quençage haut dĂ©bit a Ă©tĂ© utilisĂ© dans ce travail pour reconstruire avec des mĂ©thodes adaptĂ©es le gĂ©nomeviral entier du virus de l’hĂ©patite C (VHC) notamment pour le typer avec prĂ©cision. Une Ă©tude a ainsi permisde mettre en Ă©vidence la prĂ©sence d’une forme recombinante du VHC chez un patient. Une autre a permisde typer et dĂ©tecter les mutations de rĂ©sistance de plusieurs souches de VHC de gĂ©notypes diffĂ©rents. Enfin,une derniĂšre Ă©tude basĂ©e sur cette approche a permis de dĂ©couvrir une souche VHC appartenant Ă  un nouveausous-type. Le sĂ©quençage haut dĂ©bit a aussi Ă©tĂ© utilisĂ© dans ce travail pour dĂ©tecter des infections multiples etanalyser l’évolution virale en ciblant des gĂšnes du VHC et en mettant en Ɠuvre des mĂ©thodes non spĂ©cifiquespour 2 patients VHC sous traitement. Cette Ă©tude rĂ©trospective a permis de dĂ©finir la composition de chaqueĂ©chantillon temporel, estimer leur diversitĂ© nuclĂ©otidique, explorer la structure gĂ©nĂ©tique de la population viraleet son Ă©volution temporelle et dater les infections secondaires. Les rĂ©sultats obtenus supportent l’hypothĂšse d’unmĂ©canisme d’apparition de rĂ©sistance au traitement (selective sweeps)

    Dynamique de l’évolution intra-patient du VHC par NGS

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    High throughput sequencing of rapidly evolving hepatitis C virus populations enables large-scale studies of within-host viral heterogeneity and resistance to antiviral treatment regimes that are commonly observed in clinical cases with chronic infections. While escape from direct antiviral drugs can be explained by resistance mutations in targeted genomic regions, the absence of response to dual therapies has remained less understood. In this study we implemented amplicon sequencing to survey genomic variation at the Core and NS5B regions of HCV over a period of 13 years for two patients followed for chronic hepatitis C at Grenoble-Alpes University Hospital. From samples obtained at several time points, we observed mixed infection by multiple HCV genotypes in patients. Genetic heterogeneity and sample composition analysis provided information about the changes in viral population over the course of clinical treatment, with NS5B experiencing a sharp increase in diversity after treatment initiation compared to baseline. Evidence for HCV population genetic structure was observed in each patient, occurring in divergent lineages in phylogenetic trees. These observations point towards diversifying selection occurring post-treatment, acting on standing genomic variation and maintaining high genetic heterogeneity during infection. Being associated with treatment efficiency, the results provide the first evidence for antiviral treatment inducing soft selective sweeps in chronically infected patients with multiple HCV genotypes.Le sĂ©quençage haut dĂ©bit des populations Ă  Ă©volution rapide du virus de l’hĂ©patite C (VHC) permet des Ă©tudes Ă  grande Ă©chelle de l’hĂ©tĂ©rogĂ©nĂ©itĂ© virale intra-hĂŽte et de la rĂ©sistance aux traitements anti-viraux communĂ©ment observĂ©e en infection chronique. Alors que l’échappement au traitement anti-viral direct peut ĂȘtre expliquĂ© par des mutations de rĂ©sistance dans des rĂ©gions gĂ©nomiques ciblĂ©es, l’absence de rĂ©ponse Ă  la bithĂ©rapie (interfĂ©ron pegylĂ© et ribavirine) reste moins comprise. Dans cette Ă©tude, nous avons rĂ©alisĂ© un sĂ©quençage par amplicon pour Ă©tudier la variation gĂ©nomique des rĂ©gions Core et NS5B du VHC sur une pĂ©riode de 13 ans pour deux patients suivis pour hĂ©patite C chronique. A partir d’échantillons obtenus Ă  diffĂ©rentes dates, nous avons observĂ© chez ces patients des infections composĂ©es de plusieurs gĂ©notypes du VHC. L’hĂ©tĂ©rogĂ©nĂ©itĂ© gĂ©nĂ©tique et l’analyse de la composition des Ă©chantillons a fourni des informations sur les changements dans la population virale au cours du traitement, avec NS5B qui a connu une forte augmentation de diversitĂ© aprĂšs l’initiation du traitement. Des donnĂ©es supportant une structure gĂ©nĂ©tique de population du VHC ont Ă©tĂ© observĂ©es chez tous les patients. Ces observations orientent vers une sĂ©lection diversifiante se produisant aprĂšs traitement, agissant Ă  variation gĂ©nomique constante et maintenant une grande hĂ©tĂ©rogĂ©nĂ©itĂ© gĂ©nĂ©tique durant l’infection. AssociĂ©s Ă  l’efficacitĂ© du traitement, ces rĂ©sultats fournissent la premiĂšre preuve Ă  l’occasion d’un traitement anti-viral d’induction de «rĂ©duction de variation sĂ©lective douce» («soft selective sweeps») chez des patients infectĂ©s chroniques avec plusieurs gĂ©notypes du VHC

    PREDIMED: Clinical Data Warehouse of Grenoble Alpes University Hospital

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    International audienceGrenoble Alpes University Hospital (CHUGA) currently deploys a clinical data warehouse PREDIMED to integrate and analyze for research, education and institutional management the data of patients treated at CHUGA. In this poster, we present the methodology used to implement PREDIMED and illustrate its functionality through three first research use cases

    Hepatitis C virus whole genome sequencing: Current methods/issues and future challenges

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    International audienceTherapy for hepatitis C is currently undergoing a revolution. The arrival of new antiviral agents targeting viral proteins reinforces the need for a better knowledge of the viral strains infecting each patient. Hepatitis C virus (HCV) whole genome sequencing provides essential information for precise typing, study of the viral natural history or identification of resistance-associated variants. First performed with Sanger sequencing, the arrival of next-generation sequencing (NGS) has simplified the technical process and provided more detailed data on the nature and evolution of viral quasi-species. We will review the different techniques used for HCV complete genome sequencing and their applications, both before and after the apparition of NGS. The progress brought by new and future technologies will also be discussed, as well as the remaining difficulties, largely due to the genomic variability

    Patient 1 HCV alignments

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    16 HCV sequence alignments for patient 1 - Core and NS5B regions, 8 time samples

    Patient 3 HCV alignments

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    6 HCV sequence alignments for patient 3 - Core and NS5B regions, 3 time sample

    COVID-19 Geographical Maps and Clinical Data Warehouse PREDIMED

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    International audiencePREDIMED, Clinical Data Warehouse of Grenoble Alps University Hospital, is currently participating in daily COVID-19 epidemic follow-up via spatial and chronological analysis of geographical maps. This monitoring is aimed for cluster detection and vulnerable population discovery. Our real-time geographical representations allow us to track the epidemic both inside and outside the hospital
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