GESSO

Contents:

  • Introduction
    • Installation
    • Quick Start
  • Python API Reference
    • GESSO (gesso.GESSO)
      • GESSO
        • GESSO.__init__()
        • GESSO.compute_gas()
        • GESSO.htest_elevated_gas()
    • GeneSetActivityScoresReport (gesso.GeneSetActivityScoresReport)
      • GeneSetActivityScoresReport
        • GeneSetActivityScoresReport.gas_df()
        • GeneSetActivityScoresReport.gene_contributions_df()
        • GeneSetActivityScoresReport.locations_df()
        • GeneSetActivityScoresReport.plot_gas_spatial_map()
    • PermutationTestReport (gesso.PermutationTestReport)
      • PermutationTestReport
        • PermutationTestReport.gas_df()
        • PermutationTestReport.htest_df()
        • PermutationTestReport.locations_df()
        • PermutationTestReport.plot_gas_spatial_map()
        • PermutationTestReport.plot_pval_spatial_map()
        • PermutationTestReport.pval_df()

Tutorials:

  • GESSO Demo - 10x Visium BRCA Dataset
    • Gene set expression quantification with GESSO
    • Import the gesso package.
    • Configure logging (optional)
    • Load the spatial transcriptomics data.
    • Use GESSO to compute gene set activity scores
    • Use GESSO to systematically identify spots with significantly elevated gene set activity
  • GESSO Demo - Stereo-seq E12.5 Mouse Embryo Dataset
    • Gene set expression quantification on a large spatial transcriptomics dataset
    • Import the gesso package.
    • Configure logging (optional)
    • Load the spatial transcriptomics data.
    • Use GESSO to compute gene set activity scores
    • Visualize spatial maps for representative organ-system gene sets
    • Spatial gradients of GESSO activity scores
  • GESSO Demo - Visium HD Colorectal Cancer (Tumor)
    • Gene set activity quantification and pathway colocalization on a sub-cellular-resolution dataset
    • Import the gesso package.
    • Configure logging (optional)
    • Load the spatial transcriptomics data.
    • Use GESSO to compute gene set activity scores
    • Visualize spatial maps for the four paper pathways
    • Downstream: pathway colocalization in the tumor microenvironment
  • GESSO Demo - Xenium Prime Human Lymph Node Dataset
    • Gene set activity quantification and germinal-center radial composition on a single-cell-resolution spatial dataset
    • Import the gesso package.
    • Configure logging (optional)
    • Load the spatial transcriptomics data.
    • Use GESSO to compute gene set activity scores
    • Visualize spatial maps for the four paper pathways
    • Downstream analysis: radial composition of dominant pathway from GC centroids
  • GESSO Demo - CosMx Human Non-Small Cell Lung Cancer Dataset
    • Gene set activity quantification and EMT-niche analysis on a single-molecule imaging dataset
    • Import the gesso package.
    • Configure logging (optional)
    • Load the spatial transcriptomics data.
    • Use GESSO to compute gene set activity scores
    • Visualize spatial maps for the five paper pathways
    • Downstream: EMT-niche enrichment
GESSO
  • GESSO
  • View page source

GESSO

GESSO (Gene sEt activity Score analysis with Spatial lOcation) is a Python package for spatially informed gene set expression analysis.

Contents:

  • Introduction
    • Installation
    • Quick Start
  • Python API Reference
    • GESSO (gesso.GESSO)
    • GeneSetActivityScoresReport (gesso.GeneSetActivityScoresReport)
    • PermutationTestReport (gesso.PermutationTestReport)

Tutorials:

  • GESSO Demo - 10x Visium BRCA Dataset
  • GESSO Demo - Stereo-seq E12.5 Mouse Embryo Dataset
  • GESSO Demo - Visium HD Colorectal Cancer (Tumor)
  • GESSO Demo - Xenium Prime Human Lymph Node Dataset
  • GESSO Demo - CosMx Human Non-Small Cell Lung Cancer Dataset
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