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Bipartite Graphs for Visualization Analysis of Microbiome Data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027162%3A_____%2F16%3AN0000130" target="_blank" >RIV/00027162:_____/16:N0000130 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216224:14310/16:00093546 RIV/00216305:26220/16:PU119240

  • Result on the web

    <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4888752/" target="_blank" >https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4888752/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.4137/EBO.S38546" target="_blank" >10.4137/EBO.S38546</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Bipartite Graphs for Visualization Analysis of Microbiome Data

  • Original language description

    Visualization analysis plays an important role in metagenomics research. Proper and clear visualization can help researchers get their first insights into data and by selecting different features, also revealing and highlighting hidden relationships and drawing conclusions. To prevent the resulting presentations from becoming chaotic, visualization techniques have to properly tackle the high dimensionality of microbiome data. Although a number of different methods based on dimensionality reduction, correlations, Venn diagrams, and network representations have already been published, there is still room for further improvement, especially in the techniques that allow visual comparison of several environments or developmental stages in one environment. In this article, we represent microbiome data by bipartite graphs, where one partition stands for taxa and the other stands for samples. We demonstrated that community detection is independent of taxonomical level. Moreover, focusing on higher taxonomical levels and the appropriate merging of samples greatly helps improving graph organization and makes our presentations clearer than other graph and network visualizations. Capturing labels in the vertices also brings the possibility of clearly comparing two or more microbial communities by showing their common and unique parts.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    GJ - Diseases and animal vermin, veterinary medicine

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Evolutionary Bioinformatics

  • ISSN

    1176-9343

  • e-ISSN

  • Volume of the periodical

    2016

  • Issue of the periodical within the volume

    12 (Suppl 1)

  • Country of publishing house

    NZ - NEW ZEALAND

  • Number of pages

    7

  • Pages from-to

    17-23

  • UT code for WoS article

    000382989300003

  • EID of the result in the Scopus database