iMAP is an integrated framework for microbiome data analysis originally developed as part of academic research and published in BMC Bioinformatics (2019). The repository reflects the methodological structure and practical implementation of the pipeline at the time of publication.
Following publication, iMAP was modularized into step-based components to improve reproducibility and clarity. Some parts remain incomplete or exploratory, particularly in visualization and statistical interpretation, reflecting the evolving nature of the work rather than a finalized software release.
Current and future extensions of visualization, interpretation, and workflow design are being developed through Complex Data Insights (CDI), with a stronger emphasis on result interpretation, reasoning, and reproducible analytical structure.
This repository remains the canonical reference for the original iMAP methodology and its decomposition into pipeline stages.
| IMAP-Repo | Description | GH-Pages |
|---|---|---|
| OVERVIEW | IMAP project overview | Link |
| PART 01 | Software requirements for microbiome data analysis with Snakemake workflows | Link |
| PART 02 | Downloading and exploring microbiome sample metadata from SRA Database | Link |
| PART 03 | Downloading and filtering microbiome sequencing data from SRA database | Link |
| PART 04 | Quality control of microbiome next-generation sequencing reads | Link |
| PART 05 | Microbial profiling using MOTHUR and Snakemake workflows | Link |
| PART 06 | Microbial profiling using QIIME2 and Snakemake workflows | Link |
| PART 07 | Processing output from 16S-based microbiome bioinformatics pipelines | Link |
| PART 08 | Exploratory analysis of processed 16S-based microbiome data | Link |
| PART 09 | Statistical analysis of processed 16S-based microbiome data | Link |
| PART 10 | Machine learning analysis of processed 16S-based microbiome data | Link |
Please consider citing the iMAP article (see below) if you find any part of the IMAP practical user guides helpful in your microbiome data analysis.
Buza, T. M., Tonui, T., Stomeo, F., Tiambo, C., Katani, R., Schilling, M., … Kapur, V. (2019). iMAP: An integrated bioinformatics and visualization pipeline for microbiome data analysis. BMC Bioinformatics, 20. https://doi.org/10.1186/S12859-019-2965-4
Please, help to increase awareness of freely available microbiome data analysis tools. Current iMAP manuscript dimensions
- See this Docker README for step-by-step instructions.
- Requires Docker Images and Docker containers CLI.
- Uses fewer resources, but memory-intensive computing may sometimes fail.
- All analyses are run interactively on the container's Command-line.
- The iMAP folder is, by default, the working directory and is readable from the container.
- The output is stored in the working directory, which means it can be accessed outside the container.
- Important: Graphical applications don't work well in Docker containers.
- Some R-packages installed perfectly in RStudio may not install correctly in docker images.
- See Original README for step-by-step instructions.
- This README is a work in progress. Please visit this page regularly for more updates.
- No Docker images are required.
- May probably require manual installation of some tools.
- Uses RStudio to install required R-packages.