mbX: An R Package for Streamlined Microbiome Analysis
Here, we introduce the mbX package: an R-based tool designed to streamline 16S rRNA gene microbiome data analysis following taxonomic classification. It automates key post-sequencing steps, including taxonomic data cleaning and visualization, addressing the need for reproducible and user-friendly mi...
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MDPI AG
2025-05-01
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| author | Utsav Lamichhane Jeferson Lourenco |
| author_facet | Utsav Lamichhane Jeferson Lourenco |
| author_sort | Utsav Lamichhane |
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| description | Here, we introduce the mbX package: an R-based tool designed to streamline 16S rRNA gene microbiome data analysis following taxonomic classification. It automates key post-sequencing steps, including taxonomic data cleaning and visualization, addressing the need for reproducible and user-friendly microbiome workflows. mbX’s core functions, ezclean and ezviz, take raw taxonomic output (such as those from QIIME 2) and sample metadata to produce a cleaned relative abundance dataset and high-quality stacked bar plots with minimal manual intervention. We validated mbX on 14 real microbiome datasets, demonstrating significant improvements in efficiency and consistency of post-processing of DNA sequence data. The results show that mbX ensures uniform taxonomic formatting, eliminates common manual errors, and quickly generates publication-ready figures, greatly facilitating downstream analysis. For a dataset with 20 samples, both functions of mbX ran in less than 1 s and used less than 1 GB of memory. For a dataset with more than 1170 samples, the functions ran within 125 s and used less than 4.5 GB of memory. By integrating seamlessly with existing pipelines and emphasizing automation, mbX fills a critical gap between sequence classification and statistical analysis. An upcoming version will have an added function which will further extend mbX to automated statistical comparisons, aiming for an end-to-end microbiome analysis solution by integrating mbX with currently available pipelines. This article presents the design of mbX, its workflow and features, and a comparative discussion positioning mbX relative to other microbiome bioinformatics tools. The contributions of mbX highlight its significance in accelerating microbiome research through reproducible and streamlined data analysis. |
| format | Article |
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| institution | Kabale University |
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| language | English |
| publishDate | 2025-05-01 |
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| spelling | doaj-art-bcb5aabfa8fe431895d8d3ffe2c06f2b2025-08-20T03:29:44ZengMDPI AGStats2571-905X2025-05-01824410.3390/stats8020044mbX: An R Package for Streamlined Microbiome AnalysisUtsav Lamichhane0Jeferson Lourenco1Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USADepartment of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USAHere, we introduce the mbX package: an R-based tool designed to streamline 16S rRNA gene microbiome data analysis following taxonomic classification. It automates key post-sequencing steps, including taxonomic data cleaning and visualization, addressing the need for reproducible and user-friendly microbiome workflows. mbX’s core functions, ezclean and ezviz, take raw taxonomic output (such as those from QIIME 2) and sample metadata to produce a cleaned relative abundance dataset and high-quality stacked bar plots with minimal manual intervention. We validated mbX on 14 real microbiome datasets, demonstrating significant improvements in efficiency and consistency of post-processing of DNA sequence data. The results show that mbX ensures uniform taxonomic formatting, eliminates common manual errors, and quickly generates publication-ready figures, greatly facilitating downstream analysis. For a dataset with 20 samples, both functions of mbX ran in less than 1 s and used less than 1 GB of memory. For a dataset with more than 1170 samples, the functions ran within 125 s and used less than 4.5 GB of memory. By integrating seamlessly with existing pipelines and emphasizing automation, mbX fills a critical gap between sequence classification and statistical analysis. An upcoming version will have an added function which will further extend mbX to automated statistical comparisons, aiming for an end-to-end microbiome analysis solution by integrating mbX with currently available pipelines. This article presents the design of mbX, its workflow and features, and a comparative discussion positioning mbX relative to other microbiome bioinformatics tools. The contributions of mbX highlight its significance in accelerating microbiome research through reproducible and streamlined data analysis.https://www.mdpi.com/2571-905X/8/2/4416S rRNAbar plotmicrobiotataxonomyvisualization |
| spellingShingle | Utsav Lamichhane Jeferson Lourenco mbX: An R Package for Streamlined Microbiome Analysis Stats 16S rRNA bar plot microbiota taxonomy visualization |
| title | mbX: An R Package for Streamlined Microbiome Analysis |
| title_full | mbX: An R Package for Streamlined Microbiome Analysis |
| title_fullStr | mbX: An R Package for Streamlined Microbiome Analysis |
| title_full_unstemmed | mbX: An R Package for Streamlined Microbiome Analysis |
| title_short | mbX: An R Package for Streamlined Microbiome Analysis |
| title_sort | mbx an r package for streamlined microbiome analysis |
| topic | 16S rRNA bar plot microbiota taxonomy visualization |
| url | https://www.mdpi.com/2571-905X/8/2/44 |
| work_keys_str_mv | AT utsavlamichhane mbxanrpackageforstreamlinedmicrobiomeanalysis AT jefersonlourenco mbxanrpackageforstreamlinedmicrobiomeanalysis |