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Methods Mol Biol. 2018;1807:21-35. doi: 10.1007/978-1-4939-8561-6_3.

Online Interactive Microbial Classification and Geospatial Distributional Analysis Using BioAtlas.

Author information

1
Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark.
2
University of Southern Denmark, Odense, Denmark.
3
Technical University of Munich, Munich, Germany.

Abstract

In recent decades, the accumulation of data on 16s ribosomal RNA genes has yielded free and public databases such as SILVA, GreenGenes, The Ribosomal Database Project, and IMG, handling massive amounts of raw data and meta information. 16s rRNA gene contains hypervariable regions with great classification power. As a result, numerous classification tools have emerged including state-of-the-art tools such as Mothur, Qiime, and the 16s classifier. However, there is a gap between the sequence databases, the taxonomy profiling tools and available meta information such as geo/body-location information. Here, we present BioAtlas, and interactive web tool for searching, exploring, and analyzing prokaryotic distributions by integration of various resources of metagenomics databases. In the following section we show how to use BioAtlas to (1) search and explore prokaryote occurrences across the geospatial map of the world, (2) investigate and hunt for occurrences across generic user-generated surface-specific maps, with an example map of a human female, with data from Bouslimani et al., and (3) classify a user-given sequences dataset through our online platform for visual exploration of the spatial abundances of the identified microbes.

KEYWORDS:

16s gene; Data mining; Distributional analysis; Integration; Maps; Metadata; Microbiology; Online tool; Ribosomal RNA; Taxonomic classification

PMID:
30030801
DOI:
10.1007/978-1-4939-8561-6_3
[Indexed for MEDLINE]

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