🧪 mcmicroprep 🚀
A command-line tool for preparing multiplexed imaging datasets (🦠 Olympus, 🩸 RareCyte) for the MCMICRO Nextflow pipeline.
🛠️ Installation
-
Prerequisites
- Conda or Miniconda installed 🐍
- Python 3.10+ environment 🌟
- SLURM & Nextflow (
labsyspharm/mcmicro) on your$PATH
-
Create Conda env
conda create -n mcmicroprep python=3.12 conda activate mcmicroprep
-
Install package
pip install mcmicroprep
📁 Expected Dataset Structure
Your dataset root should contain one subdirectory per slide. Structures vary by vendor:
🦠 Olympus
Each slide directory must contain at least one *_frames/ folder (at any depth) —-- this is the minimum required structure. Additional files or folders may be present and do not need to be removed.
Important: For stitching/registration, each image (per cycle) should have exactly one *_frames/ folder. If you have multiple ROIs, separate them into separate image folders before running the pipeline; otherwise stitching/registration will produce non-legible results.
.DATASET FOLDER
├── slide1/
│ ├── cycle1_frames/
│ ├── cycle2_frames/
├── slide2/
└── slideN/
After running for Olympus, the dataset is reorganized into:
DATASET/
├── raw/
│ ├── slide1/ # non-Overview image*_frames/
│ ├── slide2/
│ └── slideN/
├── misc_files/
│ ├── slide1/ # everything else (+ Overview *_frames/)
│ ├── slide2/
│ └── slideN/
├── mcmicro_template.sh # Nextflow template
├── base.config
├── markers.csv
└── params.yml
🩸 RareCyte
Slide dirs may contain *.rcpnl at any depth: —-- this is the minimum required structure. Additional files or folders may be present and do not need to be removed.
/path/to/dataset/
├── slide1/
│ ├── img001.rcpnl
│ ├── subA/img002.rcpnl
│ └── other files
└── slideN/
After running for RareCyte, the dataset is reorganized into:
DATASET/
├── raw/
│ ├── slide1/ # all .rcpnl files (flattened)
│ ├── slide2/
│ └── slideN/
├── misc_files/
│ ├── slide1/ # everything else
│ ├── slide2/
│ └── slideN/
├── mcmicro_template.sh
├── base.config
├── markers.csv
└── params.yml
🚀 Usage
Note: Configured for the HMS O2 cluster (SLURM). Generalize by editing SLURM directives in
templates/common/.
Optional: use --input-stage registered for existing registration/*.ome.tif[f] outputs, --profile <profile> to override O2LSP, or --profile MGB for Nucleus.
🦠 Olympus
preparemcmicro \
--microscope olympus \
--image-root /path/to/dataset
🩸 RareCyte
preparemcmicro \
--microscope rarecyte \
--image-root /path/to/dataset
🛠️ Next Steps for Users
- ✏️ Edit
markers.csvin the dataset root to include your experiment-specific cycle-to-marker mappings. - 📤 Upload the entire processed dataset folder to the O2 cluster if you ran this locally.
- 🚀 Start the job on O2:
cd /n/scratch/users/${USER:0:1}/$USER/<DATASET FOLDER> sbatch mcmicro_template.sh
Happy processing! 🔬
Metadata
Release files for mcmicroprep 0.2.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mcmicroprep-0.2.4.tar.gz | 8.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mcmicroprep-0.2.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 24.1 kB
Release files / mcmicroprep-0.2.4.tar.gz
| Download URL | mcmicroprep-0.2.4.tar.gz |
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| Size | 8.7 kB |
| Tags | Source |
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| Tags | Python 3 |
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