2017
DOI: 10.1186/s12859-017-1763-0
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Visibiome: an efficient microbiome search engine based on a scalable, distributed architecture

Abstract: BackgroundGiven the current influx of 16S rRNA profiles of microbiota samples, it is conceivable that large amounts of them eventually are available for search, comparison and contextualization with respect to novel samples. This process facilitates the identification of similar compositional features in microbiota elsewhere and therefore can help to understand driving factors for microbial community assembly.ResultsWe present Visibiome, a microbiome search engine that can perform exhaustive, phylogeny based s… Show more

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Cited by 3 publications
(3 citation statements)
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“…Their approach relies on specific hardware (GPUs) to achieve low latency results for queries. The authors of Reference 14 built Visibiome , a scalable search architecture for microbiomes. Their solution is a distributed web application that only scales horizontally when dealing with increased number of parallel queries.…”
Section: Related Workmentioning
confidence: 99%
“…Their approach relies on specific hardware (GPUs) to achieve low latency results for queries. The authors of Reference 14 built Visibiome , a scalable search architecture for microbiomes. Their solution is a distributed web application that only scales horizontally when dealing with increased number of parallel queries.…”
Section: Related Workmentioning
confidence: 99%
“…We finally compared our local samples to the entire dataset using Visibiome (Azman et al (2017)), a UniFrac based search engine for microbial communities. Remarkably, no matches for sabkha were found during an exhaustive search using the popular phylogeny-based distance measure, despite the database containing 35 samples from hypersaline environments, 36 of which have at least 50 OTUs (see Table 1).…”
Section: Figurementioning
confidence: 99%
“…We calculated the ecosystem entropy to be in the midrange, rather than in the lower or higher extremes. 278 We finally compared our local samples to the entire dataset using Visibiome (Azman et al (2017) Table 3. Ecosystem entropy and additional information for selected saline samples.…”
mentioning
confidence: 99%