KNN normalization

KNN normalization#

Tests Documentation

https://raw.githubusercontent.com/javier-marchena-hurtado/KNN_normalization/main/images/KNN_normalization_logo.png

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

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