Web App Guide#
This guide documents the Cellucid web app UI end-to-end: how to load data, navigate, filter, analyze, export figures, share sessions, and troubleshoot.
If you are looking for Python-side APIs (prepare, serve, show_anndata, hooks), start with Python Package Guide instead.
Where to start (pick one)#
First time using Cellucid → Landing / Orientation Pages (Start Here) then Data Loading in the Web App (All Paths)
“I just need to load my dataset” → Data Loading in the Web App (All Paths)
“I need to understand filtering + selection” → Filtering (Visibility, Outliers, and Filter Stacks) and Highlighting and Selection (Groups, Pages, Tools)
“I want RNA velocity / vector overlays” → Vector Field / Velocity Overlay (GPU Particle Overlay)
“I want community annotation workflows” → Community Annotation (Voting + Consensus; GitHub Sync)
“Something is broken” → Troubleshooting (Web App): Start Here
Chapters (what each folder contains)#
Getting started#
What Cellucid is, system requirements, a 60-second tour, and how to choose a workflow.
All supported loading paths (exports, file picker, server mode, Jupyter), plus dataset identity, format expectations, and troubleshooting (includes vector fields where relevant).
Core UI workflows#
Navigation, selection primitives, and the “mental model” of interacting with points in the viewer.
How Cellucid treats obs fields, categorical vs continuous coloring, legends, and common field pitfalls.
Filtering mental model, UI controls, and edge cases (including “why did my selection disappear?”).
Selecting points, highlighting, synchronization rules, and how to reason about “active vs visible vs selected”.
How cross-highlighting works across viewers/embeddings and how to debug mismatches.
Analysis panel workflows (e.g. marker genes / differential expression), interpretation guidance, and troubleshooting.
Specialized features#
Enable overlays, choose fields per dimension, tune parameters, and troubleshoot missing/incorrect velocity visuals.
How multi-user annotation voting works, author setup, annotator workflows, and UI reference.
Export UI walkthrough, formats, quality knobs, metadata/provenance, and edge cases for publication-ready figures.
Saving/restoring UI state, share links, collaboration patterns, and “what makes a session compatible”.
Performance, safety, and maintenance#
Performance mental model, best practices for large datasets, and how to diagnose GPU/rendering bottlenecks.
Accessibility guidance plus a practical privacy/security model for “browser ↔ server ↔ data”.
Architecture notes, state/event model, debugging playbooks, and extension points for contributors.
Symptom → diagnosis → fix across installation, data loading, rendering, selection, analysis, and export.
One place to capture/track screenshots referenced across the web app docs.