Dataset Information

BiomMiner: An advanced exploratory microbiome analysis and visualization pipeline.

ABSTRACT: Current microbiome applications require substantial bioinformatics expertise to execute. As microbiome clinical diagnostics are being developed, there is a critical need to implement computational tools and applications that are user-friendly for the medical community to understand microbiome correlation with the health. To address this need, we have developed BiomMiner (pronounced as "biominer"), an automated pipeline that provides a comprehensive analysis of microbiome data. The pipeline finds taxonomic signatures of microbiome data and compiles actionable clinical report that allows clinicians and biomedical scientists to efficiently perform statistical analysis and data mining on the large microbiome datasets. BiomMiner generates web-enabled visualization of the analysis results and is specifically designed to facilitate the use of microbiome datasets in clinical applications.

SUBMITTER: Shamsaddini A

PROVIDER: S-EPMC7302521 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

BiomMiner: An advanced exploratory microbiome analysis and visualization pipeline.

Shamsaddini Amirhossein A Dadkhah Kimia K Gillevet Patrick M PM

PloS one 20200618 6

Current microbiome applications require substantial bioinformatics expertise to execute. As microbiome clinical diagnostics are being developed, there is a critical need to implement computational tools and applications that are user-friendly for the medical community to understand microbiome correlation with the health. To address this need, we have developed BiomMiner (pronounced as "biominer"), an automated pipeline that provides a comprehensive analysis of microbiome data. The pipeline finds ...[more]

PMID: 32555605

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Project description:BACKGROUND:One of the major challenges facing investigators in the microbiome field is turning large numbers of reads generated by next-generation sequencing (NGS) platforms into biological knowledge. Effective analytical workflows that guarantee reproducibility, repeatability, and result provenance are essential requirements of modern microbiome research. For nearly a decade, several state-of-the-art bioinformatics tools have been developed for understanding microbial communities living in a given sample. However, most of these tools are built with many functions that require an in-depth understanding of their implementation and the choice of additional tools for visualizing the final output. Furthermore, microbiome analysis can be time-consuming and may even require more advanced programming skills which some investigators may be lacking. RESULTS:We have developed a wrapper named iMAP (Integrated Microbiome Analysis Pipeline) to provide the microbiome research community with a user-friendly and portable tool that integrates bioinformatics analysis and data visualization. The iMAP tool wraps functionalities for metadata profiling, quality control of reads, sequence processing and classification, and diversity analysis of operational taxonomic units. This pipeline is also capable of generating web-based progress reports for enhancing an approach referred to as review-as-you-go (RAYG). For the most part, the profiling of microbial community is done using functionalities implemented in Mothur or QIIME2 platform. Also, it uses different R packages for graphics and R-markdown for generating progress reports. We have used a case study to demonstrate the application of the iMAP pipeline. CONCLUSIONS:The iMAP pipeline integrates several functionalities for better identification of microbial communities present in a given sample. The pipeline performs in-depth quality control that guarantees high-quality results and accurate conclusions. The vibrant visuals produced by the pipeline facilitate a better understanding of the complex and multidimensional microbiome data. The integrated RAYG approach enables the generation of web-based reports, which provides the investigators with the intermediate output that can be reviewed progressively. The intensively analyzed case study set a model for microbiome data analysis.

Project description:BackgroundThe drive to understand how microbial communities interact with their environments has inspired innovations across many fields. The data generated from sequence-based analyses of microbial communities typically are of high dimensionality and can involve multiple data tables consisting of taxonomic or functional gene/pathway counts. Merging multiple high dimensional tables with study-related metadata can be challenging. Existing microbiome pipelines available in R have created their own data structures to manage this problem. However, these data structures may be unfamiliar to analysts new to microbiome data or R and do not allow for deviations from internal workflows. Existing analysis tools also focus primarily on community-level analyses and exploratory visualizations, as opposed to analyses of individual taxa.ResultsWe developed the R package "tidyMicro" to serve as a more complete microbiome analysis pipeline. This open source software provides all of the essential tools available in other popular packages (e.g., management of sequence count tables, standard exploratory visualizations, and diversity inference tools) supplemented with multiple options for regression modelling (e.g., negative binomial, beta binomial, and/or rank based testing) and novel visualizations to improve interpretability (e.g., Rocky Mountain plots, longitudinal ordination plots). This comprehensive pipeline for microbiome analysis also maintains data structures familiar to R users to improve analysts' control over workflow. A complete vignette is provided to aid new users in analysis workflow.ConclusionstidyMicro provides a reliable alternative to popular microbiome analysis packages in R. We provide standard tools as well as novel extensions on standard analyses to improve interpretability results while maintaining object malleability to encourage open source collaboration. The simple examples and full workflow from the package are reproducible and applicable to external data sets.

Dataset Information

BiomMiner: An advanced exploratory microbiome analysis and visualization pipeline.

Publications

BiomMiner: An advanced exploratory microbiome analysis and visualization pipeline.

Similar Datasets

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