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Kvik: three-tier data exploration tools for flexible analysis of genomic data in epidemiological studies

Permanent lenke
https://hdl.handle.net/10037/8813
DOI
https://doi.org/10.12688/f1000research.6238.2
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Åpne
article.pdf (1.066Mb)
Publisher`s version (PDF)
Dato
2015-03-30
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Forfatter
Fjukstad, Bjørn; Olsen, Karina Standahl; Jareid, Mie; Lund, Eiliv; Bongo, Lars Ailo
Sammendrag
Kvik is an open-source system 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. Existing data exploration tools do not provide all the required functionality for such multi-study data exploration. We have therefore developed the Kvik framework which makes it easy to implement specialized data exploration tools for specific projects. Applications in Kvik follow the three-tier architecture commonly used in web applications, with REST interfaces between the tiers. This makes it easy to adapt the applications to new statistical analyses, metadata, and visualizations. Kvik uses R to perform on-demand data analyses when researchers explore the data. In this note, we describe how we used Kvik to develop the Kvik Pathways application to explore gene expression data from healthy women with high and low plasma ratios of essential fatty acids using biological pathway visualizations. Researchers interact with Kvik Pathways through a web application that uses the JavaScript libraries Cytoscape.js and D3. We use Docker containers to make deployment of Kvik Pathways simple.
Beskrivelse
Published version. Source at https://doi.org/10.12688/f1000research.6238.1.
Er en del av
Version 2 of this article is part of:

Fjukstad, B. (2018). Toward Reproducible Analysis and Exploration of High-Throughput Biological Datasets. Doctoral thesis. http://hdl.handle.net/10037/14576.

Forlag
F1000 Research Ltd.
Sitering
Fjukstad, B., Olsen, K.S., Jareid, M., Lund, E. & Bongo, L.A. (2015). Kvik: three-tier data exploration tools for flexible analysis of genomic data in epidemiological studies [version 1; referees: 2 approved with reservations]. F1000Research, 4:81. https://doi.org/10.12688/f1000research.6238.1
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