Abstract
BackgroundDeciphering taxonomical structures based on high dimensional sequencing data is still challenging in metagenomics study. Moreover, the common workflow processed in this field fails to identify microbial communities and their effect on a specific disease status. Even the relationships and interactions between different bacteria in a microbial community keep unknown.ResultsMetaTopics can efficiently extract the latent microbial communities which reflect the intrinsic relations or interactions among several major microbes. Furthermore, a quantitative measurement, Quetelet Index, is defined to estimate the influence of a latent sub-community on a certain disease status for given samples. An analysis of our in-house oral metagenomics data and public gut microbe data was presented to demonstrate the application and usefulness of MetaTopics. To preset a user-friendly R package, we have built a dedicated website, https://github.com/bm2-lab/MetaTopics, which includes free downloads, detailed tutorials and illustration examples.ConclusionsMetaTopics is the first interactive R package to integrate the state-of-arts topic model derived from statistical learning community to analyze and visualize the metagenomics taxonomy data.
Highlights
Deciphering taxonomical structures based on high dimensional sequencing data is still challenging in metagenomics study
We made a perfect analogy between text mining and microbial community detection, where documents can be analogized to the samples in metagenomics study and the words frequency in a document can be analogized to the OTUs abundance for a given sample
Data descriptions and preprocessing As an example, MetaTopics was firstly applied on the inhouse oral metagenomics dataset which contains 39 oral human samples. 23 of these samples are patients with two subtypes of oral lichen planus (OLP, 9 OLP_nonerosive and 14 OLP_erosive) and 16 of them are controls
Summary
MetaTopics can efficiently extract the latent microbial communities which reflect the intrinsic relations or interactions among several major microbes. A quantitative measurement, Quetelet Index, is defined to estimate the influence of a latent sub-community on a certain disease status for given samples. An analysis of our in-house oral metagenomics data and public gut microbe data was presented to demonstrate the application and usefulness of MetaTopics. To preset a user-friendly R package, we have built a dedicated website, https://github. Com/bm2-lab/MetaTopics, which includes free downloads, detailed tutorials and illustration examples To preset a user-friendly R package, we have built a dedicated website, https://github. com/bm2-lab/MetaTopics, which includes free downloads, detailed tutorials and illustration examples
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