cellxgene-census
ebezzi/readthedocs-plausible
  • Installation
  • What is SOMA
  • Python API
  • R API
  • Schema
  • Examples
    • API
      • Axis Query Example
      • Computing on X: using online algorithms
      • Census datasets presence
      • Census Datasets example
      • Census query & extract subsets
      • Census - demo ScanPy rank_gene_groups
      • Census summary cell counts example
    • Analysis
      • Learning about the CELLxGENE Census
      • Integration of data from the Census
      • Exploring all data from a tissue in the Census
      • Normalizing full-length gene sequencing data from the Census
      • Querying and fetching data from the Census
cellxgene-census
  • Examples
  • Edit on GitHub

Examples¶

API¶

  • Axis Query Example
    • Opening the Census
    • Summarize Census cell metadata
    • Full census stats
  • Computing on X: using online algorithms
    • Simple incremental (aka “online”) calculations
    • Complex online calculations
    • A more complex example - counting cells per feature, grouped by dataset_id
  • Census datasets presence
    • Is a feature present in a dataset?
    • What datasets contain a feature?
    • What features are in a dataset?
  • Census Datasets example
  • Census query & extract subsets
  • Census - demo ScanPy rank_gene_groups
  • Census summary cell counts example

Analysis¶

  • Learning about the CELLxGENE Census
    • Contents
    • Opening the Census
    • Census organization
    • Census summary content tables
    • Cell metadata
    • Gene metadata
    • Understanding Census contents beyond the summary tables
  • Integration of data from the Census
    • Finding and fetching data from mouse liver
    • Gene-length normalization of Smart-Seq2 data.
    • Integration with scvi-tools
  • Exploring all data from a tissue in the Census
    • Learning about the lung data in the Census
    • Fetching a sample of all human lung data from the Census.
  • Normalizing full-length gene sequencing data from the Census
    • Contents
    • Opening the census
    • Fetching full-length example sequencing data (Smart-Seq)
    • Normalizing expression to account for gene length
    • Validation through clustering analysis
  • Querying and fetching data from the Census
    • Contents
    • Opening the census
    • Querying cell metadata (obs)
    • Querying gene metadata (var)
    • Querying expression data
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