NicEL

NicE-view Learning for quantification of Chromatin Accessibility

Installation

pip install -r requirements.txt

Usage

Process Single File

python acicalc.py /path/to/image.czi

Process Folder

python acicalc.py -f /path/to/folder/

Get Help

python acicalc.py --help

Outputs (per .czi file)

File	Content
<name>_mask1.png	Cell segmentation mask (channel 1)
<name>_mask2.png	Cell segmentation mask (channel 2)
<name>_cell_wise.csv	Per-cell measurements

CSV Columns

Channel 1: Accessible Chromatin labeling (fluorescence, Texas Red etc)

Channel 2: DNA labeling (DAPI/Hoechst)

• cell_id - Cell identifier
• channel1_mean - Mean intensity (ch1)
• channel2_mean - Mean intensity (ch2)
• channel1_max - Max intensity (ch1)
• channel2_max - Max intensity (ch2)
• area_channel1_mask - Mask area (pixels)
• area_channel2_mask - Mask area (pixels)
• ACI_ratio - ch2_max / ch1_min

Requirements

• helper.py in Python path
• parameters.yaml
• CUDA for GPU acceleration (optional)

Key Settings

• DPI: 150 (line 53)
• Colormap: nipy_spectral (line 54)
• Folder mode: Non-recursive
• Deep Learning model: Defined in parameters.yaml