Saved in:
| Main Author: | |
|---|---|
| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2025
|
| Online Access: | https://doi.org/10.5281/zenodo.17913083 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- <h1>Release v5.0.0 (2025-12-12)</h1> <h2>Summary</h2> <p>Version 5 is a major upgrade over v4, shifting to a more robust <strong>fluorescence-first, standalone</strong> segmentation + quantification workflow (no deep learning), while <strong>significantly expanding marker compartmentalization and multi-marker co-localization reporting</strong>.</p> <h2>Key upgrades (v4 → v5)</h2> <h3>1) Segmentation robustness and consistency</h3> <ul> <li><strong>Stricter nuclear segmentation</strong> (background suppression + stronger shape/quality filtering) to reduce junk nuclei and stabilize downstream cell splitting.</li> <li><strong>Adaptive coarse cell mask</strong> generation to handle variable signal levels and imaging conditions more reliably.</li> <li>Continued use of <strong>watershed + contour refinement</strong>, plus <strong>nucleus-anchored post-processing</strong> to enforce biologically consistent cell/nucleus assignments.</li> </ul> <h3>2) Marker handling (3.tiff / 3*.tiff)</h3> <ul> <li>Preserves support for <strong>single-marker (3.tiff)</strong> and <strong>multi-marker (3X.tiff)</strong> layouts, enabling per-marker quantification and pairwise analyses when multiple markers are present.</li> </ul> <h3>3) Enriched per-marker nuclear vs cytoplasmic quantification</h3> <p>For each marker channel, v5 explicitly reports:</p> <ul> <li><strong>Nuclear and cytoplasmic expression</strong> (integrated and mean),</li> <li><strong>% localization</strong> (nuclear vs cytoplasmic),</li> <li><strong>Nuclear-to-cytoplasmic (N/C) ratios</strong>, including background-subtracted variants.</li> </ul> <h3>4) Expanded multi-marker co-localization metrics (when ≥2 markers exist)</h3> <p>v4 already computed <strong>per-cell</strong> Pearson correlation + overlap fractions. v5 upgrades this to a broader co-localization suite (computed across <strong>cell, nucleus, and cytoplasm</strong> masks), including:</p> <ul> <li><strong>Pearson r</strong>, <strong>Spearman ρ</strong></li> <li><strong>Overlap coefficient</strong></li> <li><strong>Manders M1/M2</strong></li> <li><strong>Overlap pixel %</strong></li> <li><strong>Intensity Correlation Quotient (ICQ)</strong></li> </ul> <h3>5) Library/API compatibility hardening</h3> <ul> <li>Adds compatibility handling around morphological snake/active-contour function signatures across scikit-image versions (notably iteration-parameter standardization patterns).</li> </ul> <h2>Output / CSV schema notes (impact to downstream analysis)</h2> <ul> <li><strong>v4</strong> included an "enhanced analysis" layer (normalizations, SNR fields, localization classes, QC/exclusion flags, and structured column ordering).</li> <li><strong>v5</strong> emphasizes <strong>direct, compartment-resolved marker quantification</strong> plus <strong>richer co-localization</strong>, which changes/expands the per-marker and per-pair column families (notably adding nuclear/cytoplasm % localization and expanded co-localization metrics).</li> </ul> <h2>Practical migration guidance</h2> <ul> <li>If you have scripts parsing <code>cell_measurements.csv</code>, update them to:<ul> <li>ingest the new <strong>per-marker localization (%) and N/C ratio</strong> columns, and</li> <li>(when multiple markers exist) ingest the new <strong>pairwise co-localization</strong> columns, now stratified by <strong>cell/nucleus/cytoplasm</strong> contexts.</li> </ul> </li> </ul>