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Kvik: three-tier data exploration tools for flexible analysis of genomic data in epidemiological studies.
Fjukstad, Bjørn; Standahl Olsen, Karina; Jareid, Mie; Lund, Eiliv; Bongo, Lars Ailo.
Afiliación
  • Fjukstad B; Department of Computer Science, UiT - The Arctic University of Norway, Tromsø, 9037, Norway.
  • Standahl Olsen K; Department of Community Medicine, UiT - The Arctic University of Norway, Tromsø, 9037, Norway.
  • Jareid M; Department of Community Medicine, UiT - The Arctic University of Norway, Tromsø, 9037, Norway.
  • Lund E; Department of Community Medicine, UiT - The Arctic University of Norway, Tromsø, 9037, Norway.
  • Bongo LA; Department of Computer Science, UiT - The Arctic University of Norway, Tromsø, 9037, Norway.
F1000Res ; 4: 81, 2015.
Article en En | MEDLINE | ID: mdl-26425340
ABSTRACT
Kvik is an open-source framework that we developed for explorative analysis of functional genomics data from large epidemiological studies. Creating such studies requires a significant amount of time and resources. It is therefore usual to reuse the data from one study for several research projects. Often each project requires implementing new analysis code, integration with specific knowledge bases, and specific visualizations. Although existing data exploration tools are available for single study data exploration, no tool provides all the required functionality for multistudy data exploration. We have therefore used the Kvik framework to develop Kvik Pathways, an application for exploring gene expression data in the context of biological pathways. We have used Kvik Pathways to explore data from both a cross-sectional study design and a case-control study within the Norwegian Women and Cancer (NOWAC) cohort. Kvik Pathways follows the three-tier architecture in web applications using a powerful back-end for statistical analyses and retrieval of metadata.In this note, we describe how we used the Kvik framework to develop the Kvik Pathways application. Kvik Pathways was used by our team of epidemiologists toexplore gene expression data from healthy women with high and low plasma ratios of essential fatty acids.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Observational_studies Idioma: En Revista: F1000Res Año: 2015 Tipo del documento: Article País de afiliación: Noruega

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Observational_studies Idioma: En Revista: F1000Res Año: 2015 Tipo del documento: Article País de afiliación: Noruega