MICROBIOME PIPELINE
mbXPro
Command-Line Demo · macOS, Apple Silicon
Zero dependencies — nothing to installRun the full mbX Pro 16S pipeline from the terminal with no setup. Docker, QIIME2, R, Python and the analysis image are all bundled here — you do not install anything.
cli/
├── mbXPro ← the launcher you call
├── run_demo.sh ← one-shot: runs the pipeline on the test data set
├── engine/ ← container glue script (do not edit)
└── payload/ ← bundled runtime + 4.2 GB analysis image (do not edit)
The test data lives one level up, in ../test_data_set/.
Open Terminal, drag this cli folder onto the
Terminal icon (or cd into it), then run:
./run_demo.sh
That's it. It boots the analysis engine once, then runs the complete pipeline on the bundled test samples. When it finishes, your results are in:
demo_outputs/mbX_pro_outputs_<timestamp>/
Open the report:
open demo_outputs/mbX_pro_outputs_*/18_final_report/mbX_pro_final_report.html
The simplest form — just give it your FASTQ folder and metadata file:
./mbXPro /path/to/your/FASTQ_folder /path/to/your/metadata.txt
Results are written next to your FASTQ folder, in a timestamped
mbX_pro_outputs_<date>/ folder. You can also choose where they
go by adding an output folder as a third argument:
./mbXPro /path/to/FASTQ /path/to/metadata.txt /path/to/output_location
That's all most users need — nothing to install. The first run boots the analysis engine (VM + image load) automatically.
./mbXPro run \
--fastq /path/to/your/FASTQ_folder \
--metadata /path/to/your/metadata.txt \
--out /path/to/output_location
./mbXPro prepare # just boot the VM + load the image
./mbXPro stop # shut the engine down to free RAM
./mbXPro doctor # print readiness
Note: the FASTQ folder, metadata file, and output location must all be inside your home folder (Desktop, Documents, etc.).
Pass extra mbX Pro flags after a --, e.g. publication-quality figures:
./mbXPro /path/to/FASTQ /path/to/metadata.txt -- --publication-figures
xattr -dr com.apple.quarantine ../mbXPro stop
then delete ~/.mbxpro.If mbX Pro helps your research, please cite our paper:
https://doi.org/10.3390/stats8020044
https://www.mdpi.com/2571-905X/8/2/44