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DNAism: exploring genomic datasets on the web with Horizon Charts
BACKGROUND: Computational biologists daily face the need to explore massive amounts of genomic data. New visualization techniques can help researchers navigate and understand these big data. Horizon Charts are a relatively new visualization method that, under the right circumstances, maximizes data...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4729118/ https://www.ncbi.nlm.nih.gov/pubmed/26819101 http://dx.doi.org/10.1186/s12859-016-0891-2 |
Sumario: | BACKGROUND: Computational biologists daily face the need to explore massive amounts of genomic data. New visualization techniques can help researchers navigate and understand these big data. Horizon Charts are a relatively new visualization method that, under the right circumstances, maximizes data density without losing graphical perception. RESULTS: Horizon Charts have been successfully applied to understand multi-metric time series data. We have adapted an existing JavaScript library (Cubism) that implements Horizon Charts for the time series domain so that it works effectively with genomic datasets. We call this new library DNAism. CONCLUSIONS: Horizon Charts can be an effective visual tool to explore complex and large genomic datasets. Researchers can use our library to leverage these techniques to extract additional insights from their own datasets. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-0891-2) contains supplementary material, which is available to authorized users. |
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