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Site Navigation

  • Guide
  • API Reference
  • Integrations
  • Changelog

Overview

  • Introduction
  • Tutorial

How to

  • Install & setup
  • Query, search & stream
    • Query & search registries
    • Slice & stream arrays
  • Track notebooks, scripts & functions
  • Curate datasets
  • Access & manage ontologies
    • Manage biological ontologies
    • Access public ontologies
      • Gene
      • Protein
      • Organism
      • CellLine
      • CellType
      • CellMarker
      • Tissue
      • Disease
      • Phenotype
      • Pathway
      • ExperimentalFactor
      • DevelopmentalStage
      • Ethnicity
  • Transfer data

Use cases

  • Access atlases
    • Arc Virtual Cell Atlas: scRNA-seq
    • Hubmap
  • Manage data types
    • scRNA-seq
      • Standardize and append a dataset
      • Query artifacts
      • Analyze a collection in memory
      • Train a machine learning model on a collection
      • Concatenate datasets to a single array store
    • Bulk RNA-seq
    • Flow cytometry
      • Append a new dataset
      • Query & integrate data
      • Analyze the collection and save a result
    • Spatial RNA-seq
      • Interactive visualization using Vitessce
      • Curate and ingest spatial data
      • Train a spatial ML model
    • Multi-modal
    • EHR
  • Leverage ontologies
    • Gene Ontology (GO)
    • CellTypist
    • Standardize metadata on-the-fly
    • RDF export & SPARQL queries
  • Trace data & code
    • Re-constructing Schmidt et al. (2022)
  • Manage computational workflows
    • Nextflow
      • nf-lamin plugin reference
      • Post-run script
    • Redun
    • Snakemake
  • Manage MLOps
    • Weights & Biases
    • MLFlow
    • Curate MNIST
    • Croissant
  • Manage visualization dashboards
    • Vitessce

The Hub

  • Manage access
  • Work with sheets
  • Security

Other topics

  • Design & architecture
  • FAQ
    • Pydantic & Pandera vs. LaminDB
    • Will data get duplicated upon re-running code?
    • Will data & metadata stay in sync?
    • Can I disable tracking run inputs?
    • How do I validate & annotate arbitrary data structures?
    • What happens if I import a schema module without lamindb?
    • Where to store external links and IDs?
    • How do I trash or archive records?
    • How to delete records?
    • Keep artifacts local in a cloud instance
    • Django field validation
    • Why should I not index datasets with gene symbols?
    • How does search work?
  • Influences
  • Glossary

Jupyter Notebook

Interactive visualization using Vitessce¶

SpatialDatasets can be visualized interactively on LaminHub using Vitessce.

Here is a guide for visualizing spatial data with Vitessce.

This notebook adds the Vitessce visualization to this Xenium dataset discussed on the previous page.

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Spatial RNA-seq

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Curate and ingest spatial data
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