ATHENA - Analysis of Tumor Heterogeneity in Spatial Omics Measurements

ATHENA is an open-source computational framework written in Python that facilitates the visualization, processing and analysis of (spatial) heterogeneity from spatial omics data. ATHENA supports any spatially resolved dataset that contains spatial transcriptomic or proteomic measurements, including Imaging Mass Cytometry (IMC), Multiplexed Ion Beam Imaging (MIBI), multiplexed Immunohistochemisty (mIHC) or Immunofluorescence (mIF), seqFISH, MERFISH, Visium.

Note

Start by reading the Quickstart tutorial.

General

• Installation

Gallery

• Overview of ATHENA
  • Main components
  • Further Resources
• Methodology
• Quickstart
  • Important
  • Requirements
  • Further Resources
  • Load Example Data
  • How to Create a SpatialOmics Instance with Dummy Data
  • Minimal Working Example
  • Sample-level Meta Data
  • Observation-level Meta Data
  • Observation-level Omics Profiles
  • Compute Graphs
  • Visualise the Data
  • Compute Metrics
  • Note On Phenotype Encodings
  • Note On Segmentation Masks
• Tutorial
  • Import needed packages
  • Load IMC data into a SpatialOmics object
  • Explore SpatialOmics object
  • Visualize raw images and masks
  • Visualize single-cell data
  • Graph construction
  • Heterogeneity quantification
• SpatialOmics Tutorial
  • Load from Raw Data
  • Load Pre-processed SpatialOmics
  • Load Pre-processed AnnData-Datasets

API

• API Overview
  • Methods
  • Datasets