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Cell Atlas Overview

Frameworks and practices for constructing scalable, interoperable reference cell atlases.

mysimulator teamUpdated June 2026≈ 3 min read▶ Open the simulation

Motivation

Cell atlases aggregate single-cell and spatial data to define reference cell types, states, and lineages across tissues and development. They underpin diagnostics and therapeutic discovery.

Data Generation

scRNA-seq, ATAC-seq, multiome

Spatial transcriptomics and proteomics

Standardized tissue acquisition and processing

Integration and Annotation

Batch correction, joint embeddings, and label transfer. Use ontologies (CL, UBERON) and consensus marker sets. Iterative expert curation remains essential.

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Spatial Context

Register cell types to histology; infer neighborhoods and niches; reconcile across donors and conditions.

Portals and Accessibility

Public portals provide query and download access; adhere to FAIR data and privacy safeguards.

Examples

Example 1: Mapping a New Dataset to a Reference

Preprocess with standard QC; compute embeddings.

Map to a reference atlas; transfer labels.

Validate with markers and differential expression.

Example 2: Building a Tissue-Specific Sub-Atlas

Aggregate public datasets; harmonize metadata.

Integrate and annotate; define consensus types.

Release with interactive portal and API.

Frequently asked questions

How are cell types defined?

By transcriptional profiles, markers, function, and lineage, grounded in ontologies.

How to reconcile annotations across studies?

Use reference mapping and consensus vocabularies; maintain provenance.

What about rare cell types?

Enrich during sampling, pool datasets, and validate with targeted assays.

How to handle batch effects?

Apply integration methods and include technical covariates in models.

How to share sensitive data?

Use controlled access and de-identification; align with regulations.

How are spatial atlases built?

Combine spatial assays with deconvolution and registration to tissue coordinates.

What QC metrics matter most?

Read counts, mitochondrial content, doublet rate, and consistency across replicates.

How to ensure reproducibility?

Version datasets, code, and annotations; publish pipelines.

What are the main challenges?

Heterogeneity, scaling integration, and harmonizing semantics.

How to keep atlases up to date?

Implement rolling ingestion, automated checks, and community contributions.

Try it live

Everything above runs in your browser — open Cell Atlas Overview: Building Reference Maps of Human Cells and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Cell Atlas Overview: Building Reference Maps of Human Cells simulation