CoCo: An application to store High-Throughput Sequencing data in compact text and binary file formats

Khanipov, Kamil; Golovko, George; Rojas, Mark; Albayrak, Levent; Dobretsberger, Otto; Pimenova, Maria; Olson, N. E.; Chumakov, S. M.; Fofanov, Yuriy

doi:10.1109/bibm.2015.7359838

Cited by 1 publication

(2 citation statements)

References 13 publications

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“…21 Shortly, in the first experiment, long-term on-farm development of cecal microbiota was described. The three chickens or hens were taken from the flock, sacrificed at weeks 1,2,3,4,8,12,16,19,22,26,34,38,45,51,55, and 60. In the second experiment, short-term development of cecal microbiota was observed in newly hatched chickens.…”

Section: Methodsmentioning

confidence: 99%

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Bipartite Graphs for Visualization Analysis of Microbiome Data

Sedlář

Vídeňská

Škutková

et al. 2016

Evol Bioinform Online

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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.

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Section: Methodsmentioning

confidence: 99%

“…It is cheaper to acquire new data by sequencing than it is to store and process them. 16 Moreover, this huge amount of sequences contains contaminations, so it is not necessary to use every sequence. 17 Rather, an overall view can be more desirable.…”

Section: Introductionmentioning

confidence: 99%