stLENS Documentation

Welcome to the stLENS documentation! stLENS is a Python-based scalable tool to determine the optimal number of principal components from the spatial transcritomics data. It is fully compatible with the scverse ecosystem.

TL;DR

Installation

   pip install stLENS

Load data

   # Load data - it is recommended to use AnnData with count data stored in X
   import scanpy as sc
   adata = sc.read_h5ad("path/to/your_data.h5ad")

Preprocessing with stLENS

    from stLENS import stLENS
    stlens = stLENS()

   # Perform filtering before the steps below.

   # Find the optimal number of principal components.
   stlens.find_optimal_pc(adata)
   # Perform PCA.
   stlens.pca(adata)

Contents