Lund Jesper, Tan Qihua, Baumbach Jan
Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark.
University of Southern Denmark, Odense, Denmark.
Methods Mol Biol. 2018;1807:21-35. doi: 10.1007/978-1-4939-8561-6_3.
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.
近几十年来，16S核糖体RNA基因数据的积累产生了诸如SILVA、GreenGenes、核糖体数据库项目和IMG等免费的公共数据库，这些数据库处理大量的原始数据和元信息。16S rRNA基因包含具有强大分类能力的高变区。因此，出现了许多分类工具，包括诸如Mothur、Qiime和16S分类器等最先进的工具。然而，序列数据库、分类学分析工具与可用的元信息（如地理/身体位置信息）之间存在差距。在这里，我们展示了BioAtlas，这是一个交互式网络工具，用于通过整合宏基因组学数据库的各种资源来搜索、探索和分析原核生物分布。在接下来的部分中，我们将展示如何使用BioAtlas来：（1）在世界地理空间地图上搜索和探索原核生物的出现情况；（2）通过通用的用户生成的特定表面地图（以人类女性的示例地图为例，数据来自Bouslimani等人）调查和寻找出现情况；以及（3）通过我们的在线平台对用户提供的序列数据集进行分类，以直观地探索已识别微生物的空间丰度。
