motility_painting

Linking live-cell-imaging (LCI) motility trajectories to Cell Painting (CP) single-cell morphology, via deck.gl + Celldega widgets.

Python · Jupyter · anywidget deck.gl · WebGL Celldega clustergram Spearman + BH-FDR Experimental overview → Engineering notes →

What is this?

~4,700 cells were imaged live for 65 timepoints (LCI), tracked into motility trajectories, then fixed and imaged again with Cell Painting (CP). A per-FOV similarity-transform alignment links each CP cell to its own motility trajectory (shared link_id), so a cell's fixed morphology can be compared directly to how it moved while alive. This site is a browsable, kernel-free view of that pipeline's widgets and findings — no notebook required.

Live, in your browser

Pick a view. Each one is a self-contained widget with no kernel attached — all interactions (scrub/play, hover, click-to-link, pan/zoom) run purely in the browser.

open standalone ↗

The dropdown swaps between the three widget pages. Each is fully self-contained (no CDN calls at page load) via a small custom static host implementing anywidget's own AFM spec — see the engineering notes for why the classic ipywidgets embedding path doesn't work here.

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