Versatile open-source tool for microbiome analysis

A list of R environment based tools for microbiome data exploration, statistical analysis and visualization

The EasyMultiProfiler package aims to offer a user-friendly and efficient multi-omics data analysis tool on the R platform. It facilitates various essential tasks related to microbiome, genome, and metabolite downstream analysis, providing a seamless workflow from start to finish.

High-resolution strain-level microbiome composition analysis tool based on reference genomes and k-mers

Ying's tools for analysis, with particular focus on microbiome data

A continually expanding collection of microbiome analysis tools

Handy tools for Microbiome analysis in R

A user-friendly tool for quality control and interactive analysis of microbiome data

tools for microbiome data analysis

A Set of Tools and Wrappers for Tidy Microbiome Analysis in R

Tools for microbiome data analysis

div-utils: tools for microbiome data analysis

WDL-based tool designed to streamline microbiome data processing for assembling, polishing, annotating, and visualizing prokaryotic genomes. It simplifies the analysis process from raw sequencing reads to high-quality annotated genomes

Here is my microbiome data analysis tutorial for using PathoScope and other tools!

Microbiome Analysis Tools for R

🧮🦠 A curated list of papers on microbiome statistical analysis and tools.

A Python CLI tool that converts NOAA FAIRe Excel metadata files into QIIME2-compatible metadata and manifest files for streamlined microbiome sequencing data analysis.

A complete pipeline for processing and analyzing Nanopore microbiome data using QIIME2. Includes quality control, taxonomic classification, diversity analysis, and result visualization. Built using R Markdown, Bash, and open-source tools.

Code to reproduce preprocessing analysis of IBD dataset from the Human Microbiome Project. This work will provide a walk through analysis tool for the scientific community with less technical knowledge on data science and machine learning.

A streamlined pipeline was developed for processing paired-end 16S rRNA reads, integrating Bash and R tools to automate microbiome analysis. This standardized, reproducible workflow reduces manual intervention and time, ensuring consistency, scalability, and efficient data processing.

Microbiome Automated Analysis Workflows：A web-based tool for multifunctional, visual analysis of microbiome data

StrainYC：a strain-level microbiome composition analysis tool.

Intelligent differential abundance analysis tool for microbiome data

Bioinformatic tool for post-processing and data analysis of microbiome SIP studies

a python-based set of tools for processing next-gen sequencing reads for microbiome analysis

Galaxy tools for Mauro Tutino's microbiome pipeline scripts https://github.com/MTutino/Amplicon_analysis

Using interpretable Machine Learning to decode the soil microbiome’s response to drought stress: Identifying marker taxa for drought stress using interpretable ML with SHAP values and conventional Differential Abundance Analysis tools.

Metagenomics pipeline for soil microbiome analysis that connects ASVs to functions (KOs) and PGPTs (plant growth–promoting traits). Based on 16S sequencing from soil bacteria, the tool helps you infer what a soil is “good at”.

Tool for Analysis of meta microbiomes and metabolomes.

Microbiome analysis tools