Evidence map›Paper›PMID 26425340›Full record

ArticleF1000Research2015

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

Bjørn Fjukstad, Karina Standahl Olsen, Mie Jareid, Eiliv Lund, Lars Ailo Bongo

Abstract read
In one paragraph

Article in F1000Research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Bjørn FjukstadDepartment of Computer Science, UiT - The Arctic University of Norway, Tromsø, 9037, Norway.
Karina Standahl OlsenDepartment of Community Medicine, UiT - The Arctic University of Norway, Tromsø, 9037, Norway.
Mie JareidDepartment of Community Medicine, UiT - The Arctic University of Norway, Tromsø, 9037, Norway.
Eiliv LundDepartment of Community Medicine, UiT - The Arctic University of Norway, Tromsø, 9037, Norway.
Lars Ailo BongoDepartment of Computer Science, UiT - The Arctic University of Norway, Tromsø, 9037, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Data explorationEpidemiological studiesFunctional genomicsKvikOn-demand data analysisOpen-source software

Identifiers

PMID26425340
PMCPMC4574765

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.