goatpy documentation

goatpy is a Python toolkit for spatial glycomics analysis, combining MALDI mass spectrometry imaging with H&E histology registration and analysis.

Getting started

• Installation
  • Requirements
  • Recommended: conda environment
  • PyPI
  • From source (latest development version)
  • Optional dependencies
  • WSI support (SVS, NDPI, CZI files)
• Getting Started with goatpy Tutorial
  • Loading and Aligning Data
  • Loading with specific m/z values
  • Adding Pathologist annotations
  • Subsetting Data
  • Saving and Loading goatpy Ojects
  • Plotting and Visualising Results
  • Tutorial Session Info

Tutorials

• Aligning Spatial Glycomics and IHC images
  • Manual Alignment
  • Automatic Alignment
  • Spatially Informed Clustering (GraphPCA)
  • Align Additional Image Layers
  • Tutorial Session Info
• Multi-Sample goatpy Analysis Tutorial
  • Loading Data
  • Data Preprocessing
  • Merging Data
  • Using scanpy function with goatpy
  • Batch Correction with goatpy
  • m/z peak glycan annotation
  • Differential Abundance Analysis
  • Comparing Pathologist Annotation

User guide

• Loading and aligning MALDI + H&E
  • Overview
  • Basic usage
  • Parameters
  • Output SpatialData structure
  • Custom peaks
  • Registration quality
• QuPath annotations
  • During registration
  • After registration
  • Exporting from QuPath
  • Accessing annotation labels
  • Visualising with spatialdata-plot
• GraphPCA and clustering
  • GraphPCA
  • K-means clustering
  • Visualising clusters as a pseudo-image
• Pseudo-image generation
  • Categorical columns
  • Continuous columns
  • Parameters
  • Output
• Landmark alignment GUI
  • Launch the GUI
  • Workflow
  • Apply the alignment
  • Multiscale images

API reference

• goatpy
  • Submodules

Development

• Changelog
• Contributing

Indices and tables

• Index

• Module Index

• Search Page