MicrobiomeBPR

MicrobiomeBPR implements standardized workflows for processing and analyzing 16S rRNA amplicon and shotgun metagenomic sequencing data to support assembly, binning, annotation, visualization, and comparative statistical analyses of microbial communities.


Key Features:

  • Dual Workflow Approach: Provides separate workflows for amplicon and metagenomic analyses to address distinct analytical requirements.
  • Amplicon Analysis Workflow: Processes 16S rRNA data using mothur and dada2 and includes standard visualization techniques for interpreted outputs.
  • Metagenomics Analysis Workflow: Integrates a suite of open-source tools covering quality control, assembly, binning, annotation, and statistical analyses for shotgun metagenomic data.
  • Controlled by Bash Scripts: Workflows are managed via bash scripts named amplicon_analysis.sh and metagenomics_analysis.sh to support reproducible execution.
  • Best-Practice Protocols and Standardization: Includes protocols for experimental design, sample processing, sequencing techniques (16S rRNA and shotgun/metagenomic), and data analysis while addressing sequencing errors and genomic repeats to mitigate methodological variability.

Scientific Applications:

  • Ecology: Characterizing microbial community composition and roles across diverse ecosystems.
  • Physiology: Investigating microbiome impacts on host health and disease processes.
  • Metabolism: Exploring metabolic pathways and functional potential mediated by environmental and host-associated microorganisms.

Methodology:

Amplicon processing employs mothur and dada2; metagenomic processing includes quality control, assembly, binning, annotation, visualization, and statistical analyses, with both workflows orchestrated by the bash scripts amplicon_analysis.sh and metagenomics_analysis.sh.

Topics

Details

License:
MIT
Tool Type:
workflow
Programming Languages:
Shell, R
Added:
1/14/2020
Last Updated:
11/24/2024

Operations

Publications

Bharti R, Grimm DG. Current challenges and best-practice protocols for microbiome analysis. Briefings in Bioinformatics. 2019;22(1):178-193. doi:10.1093/bib/bbz155. PMID:31848574. PMCID:PMC7820839.