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Animalcules: Interactive Microbiome Analytics and Visualization in R

Overview
Journal Microbiome
Publisher Biomed Central
Specialties Genetics
Microbiology
Date 2021 Mar 29
PMID 33775256
Citations 19
Authors
Affiliations
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Abstract

Background: Microbial communities that live in and on the human body play a vital role in health and disease. Recent advances in sequencing technologies have enabled the study of microbial communities at unprecedented resolution. However, these advances in data generation have presented novel challenges to researchers attempting to analyze and visualize these data.

Results: To address some of these challenges, we have developed animalcules, an easy-to-use interactive microbiome analysis toolkit for 16S rRNA sequencing data, shotgun DNA metagenomics data, and RNA-based metatranscriptomics profiling data. This toolkit combines novel and existing analytics, visualization methods, and machine learning models. For example, the toolkit features traditional microbiome analyses such as alpha/beta diversity and differential abundance analysis, combined with new methods for biomarker identification are. In addition, animalcules provides interactive and dynamic figures that enable users to understand their data and discover new insights. animalcules can be used as a standalone command-line R package or users can explore their data with the accompanying interactive R Shiny interface.

Conclusions: We present animalcules, an R package for interactive microbiome analysis through either an interactive interface facilitated by R Shiny or various command-line functions. It is the first microbiome analysis toolkit that supports the analysis of all 16S rRNA, DNA-based shotgun metagenomics, and RNA-sequencing based metatranscriptomics datasets. animalcules can be freely downloaded from GitHub at https://github.com/compbiomed/animalcules or installed through Bioconductor at https://www.bioconductor.org/packages/release/bioc/html/animalcules.html . Video abstract.

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References
1.
Arango-Argoty G, Garner E, Pruden A, Heath L, Vikesland P, Zhang L . DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data. Microbiome. 2018; 6(1):23. PMC: 5796597. DOI: 10.1186/s40168-018-0401-z. View

2.
Saulnier D, Riehle K, Mistretta T, Diaz M, Mandal D, Raza S . Gastrointestinal microbiome signatures of pediatric patients with irritable bowel syndrome. Gastroenterology. 2011; 141(5):1782-91. PMC: 3417828. DOI: 10.1053/j.gastro.2011.06.072. View

3.
Botero L, Delgado-Serrano L, Cepeda M, Bustos J, Anzola J, Del Portillo P . Respiratory tract clinical sample selection for microbiota analysis in patients with pulmonary tuberculosis. Microbiome. 2014; 2:29. PMC: 4164332. DOI: 10.1186/2049-2618-2-29. View

4.
Baldini F, Heinken A, Heirendt L, Magnusdottir S, Fleming R, Thiele I . The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities. Bioinformatics. 2018; 35(13):2332-2334. PMC: 6596895. DOI: 10.1093/bioinformatics/bty941. View

5.
Robinson M, McCarthy D, Smyth G . edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2009; 26(1):139-40. PMC: 2796818. DOI: 10.1093/bioinformatics/btp616. View