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singleCellHaystack

singleCellHaystack#

Lifecycle:beta PyPI Downloads

This repository contains a python implementation of singleCellHaystack (version >= 1.0.0).

This package is currently in beta. The most important functionality in the R package works, but some features are not yet available. Here is a (probably imcomplete) list of missing features. Some will be added in the future.

  • weights.advanced.Q (formerly known as use.advanced.sampling).

  • seeding method for calculating grid points.

  • Hierarchical clustering method for cluster_genes.

Installation#

You can install singleCellHaystack from PyPI:

pip install singleCellHaystack

Support for conda installation will be added in the future.

Example#

import scanpy as sc
import singleCellHaystack as hs

adata = sc.read_h5ad("data.h5ad")

[... process adata object ...]

res = hs.haystack(adata, basis="pca")
res.top_features(n=10)

References#

  • Our manuscript describing the updated, more generally applicable version of singleCellHaystack including this Python implementation was published in Scientific Reports.

  • Our manuscript describing the original implementation of singleCellHaystack for R (version 0.3.4) was published in Nature Communications.

If you use singleCellHaystack in your research please cite our work using:

Vandenbon A, Diez D (2023). “A universal tool for predicting differentially active features in single-cell and spatial genomics data.” Scientific Reports, 13(1), 11830. doi:10.1038/s41598-023-38965-2.

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