knn-normalization 0.1.1

Neighbor-based normalization of CITE-seq data

KNN normalization

Background and motivation

KNN normalization is a normalization method for protein counts in CITE-seq data. KNN normalization learns from neighbor cells in a KNN graph in order to estimate the appropriate total protein counts in each cell, accurately estimating total protein counts while preserving biological information.

Installation

Install the latest release of KNN_normalization from PyPI:

pip install KNN_normalization

Basic usage

import scanpy as sc
import knn_normalization as knn

# Load your CITE-seq data
adata = sc.read_h5ad("path/to/your/data.h5ad")

# Run KNN normalization (modifies adata in place)
knn.tl.knn_normalize(adata)

Documentation

Please refer to the documentation, in particular, the documentation of the knn_normalize() function.

Installing the Development Version (optional)

If you need the latest unreleased features or bug fixes:

pip install git+https://github.com/javier-marchena-hurtado/KNN_normalization.git@main

Release notes

See the changelog.

Contact

For questions and help requests, please open a discussion on GitHub. If you found a bug, please use the issue tracker.

Citation

t.b.a