Bipartite Graphs for Visualization Analysis of Microbiome Data

Kód výsledku v 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>

Nalezeny alternativní kódy

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

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Bipartite Graphs for Visualization Analysis of Microbiome Data

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Bipartite Graphs for Visualization Analysis of Microbiome Data

Popis výsledku anglicky

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.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

GJ - Choroby a škůdci zvířat, veterinární medicina

OECD FORD obor

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Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

Evolutionary Bioinformatics

ISSN

1176-9343

e-ISSN

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Svazek periodika

2016

Číslo periodika v rámci svazku

12 (Suppl 1)

Stát vydavatele periodika

NZ - Nový Zéland

Počet stran výsledku

7

Strana od-do

17-23

Kód UT WoS článku

000382989300003

EID výsledku v databázi Scopus

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