Getting Started with mAIcrobe¶

Welcome to mAIcrobe! This guide will get you up and running with bacterial cell analysis in under 10 minutes.

🚀 Installation¶

Prerequisites¶

Before installing mAIcrobe, ensure you have:

• Miniconda (strongly recommended for dependency management)

Installing Miniconda (Recommended)¶

We strongly recommend using miniconda to manage your Python environment and dependencies. This prevents conflicts and ensures a smooth installation experience.

Download and Install Miniconda¶

1. Download the appropriate installer for your system from miniconda.org:

   • Windows: Download the .exe installer
   • macOS: Download the .pkg installer (Intel) or .sh script (Apple Silicon)
   • Linux: Download the .sh script

2. Install by following the installer prompts:

   • Accept the license agreement
   • Choose installation location (default is recommended)
   • Important: When asked "Do you wish the installer to initialize Miniconda3?", choose Yes
   • Important: Do NOT install miniconda, or allow the environments to be managed, in a folder that contains spaces.

3. Restart your terminal/command prompt after installation

4. Verify installation by running the following in your terminal (macOS/Linux) or miniconda command prompt (Windows):

   conda --version
   

Create a Dedicated Environment¶

Create a clean environment specifically for mAIcrobe. In your terminal (macOS/Linux) or miniconda command prompt (Windows), run:

# Create new environment with Python 3.11
conda create -n mAIcrobe python=3.11

# Activate the environment
conda activate mAIcrobe

Recommended Installation (Using Conda)¶

With your conda environment activated, install mAIcrobe:

# Install napari-mAIcrobe with pip
pip install napari-mAIcrobe

Important Make sure your conda environment is activated whenever you want to use mAIcrobe! You should see (mAIcrobe) in your terminal prompt. \n**mAIcrobe is now installed! 🎉** To use it, just activate your conda environment and launch napari. See below for more details.

pip install napari-mAIcrobe

git clone https://github.com/HenriquesLab/mAIcrobe.git
cd mAIcrobe
pip install -e .[testing]

✅ Verify Installation¶

Test your installation by launching napari with the plugin. In your terminal, run:

# Activate your environment first (if using conda)
conda activate mAIcrobe

# Launch napari
napari

Or programmatically:

import napari
viewer = napari.Viewer()

Then check if "mAIcrobe" appears under Plugins in the menu bar.

🔥 First Analysis¶

Let's perform your first bacterial cell analysis using the included sample data.

Step 1: Launch napari¶

Go to your terminal and run:

napari

or programmatically:

import napari
viewer = napari.Viewer()

Step 2: Load Sample Data¶

mAIcrobe includes S. aureus test images. Load them via:

Option A: GUI Method 1. Go to File > Open Sample > mAIcrobe 2. Select: - "Phase contrast S. aureus" - "Membrane dye S.aureus" - "DNA dye S.aureus"

Option B: Programmatic Method

import napari
import numpy as np

# Launch napari viewer
viewer = napari.Viewer()

# Load sample data
from napari_mAIcrobe._sample_data import phase_example, membrane_example, dna_example

# Get the sample images
phase_data = phase_example()[0]
membrane_data = membrane_example()[0]
dna_data = dna_example()[0]

# Add images to viewer
phase_layer = viewer.add_image(phase_data[0], **phase_data[1])
membrane_layer = viewer.add_image(membrane_data[0], **membrane_data[1])
dna_layer = viewer.add_image(dna_data[0], **dna_data[1])

Step 3: Segment Cells¶

1. Go to Plugins > mAIcrobe > Compute label
2. Configure segmentation parameters:

   Base Image: Phase (select the phase contrast layer)
   Fluor 1: Membrane (select the membrane layer)
   Fluor 2: DNA (select the DNA layer)
   Model: Isodata (or CellPose cyto3)
   

   For the purpose of this tutorial, leave all other parameters as default.
3. Click Run

The segmentation will create a new "Labels" layer with individual cells outlined.

Step 4: Analyze Cells¶

1. Go to Plugins > mAIcrobe > Compute cells
2. Configure analysis parameters:
   • Label Image: Select the labels layer from Step 3
   • Membrane Image: Select membrane layer
   • DNA Image: Select DNA layer
   • Pixel size: Enter your pixel size (e.g., 0.065 μm/pixel) (optional)
   • Classify cell cycle: Check this box
   • Model: Select "S.aureus DNA+Membrane Epi"
3. Click Run

This will add statistical measurements to the Labels layer properties. For the purpose of this tutorial, leave all other parameters as default.

Step 5: View Results¶

After analysis completes, you can:

• View cell statistics: Check the layer properties panel
• Filter cells: Use Plugins > napari-mAIcrobe > Filter cells
• Generate reports: Enable "Generate Report" in Step 4

📚 Next Steps¶

Now that you've completed your first analysis:

1. Segmentation Guide - Choose the optimal segmentation method
2. Cell Analysis Guide - Comprehensive analysis workflows
3. Cell Classification Guide - Cell classification in detail
4. API Reference - Programmatic usage

Tip: Building your own classifier? Export per-cell training pickles via Plugins > mAIcrobe > Compute pickles. Provide a Labels layer, a Points layer named with the class id (e.g., "1"), select one/two channels, and choose an output folder. See the Cell Classification Guide for details.

🤝 Getting Help¶

If you encounter issues:

1. Check this documentation and troubleshooting guides
2. Search GitHub Issues
3. Include error messages, napari version, and system details

Welcome to the mAIcrobe community! 🔬