panhumanpy 0.5.0

A Python package for automated cell type annotation in scRNA-seq using Azimuth Neural Network.

panhumanpy

Current version: 0.5.0 (Andromeda)

A package for cell annotation using Azimuth Neural Network.

Prerequisites

• python >=3.9
• pip
• git

Installation

To install the base version of the package (with CPU support only), run:

pip install panhumanpy

or to install from GitHub, run:

pip install git+https://github.com/satijalab/panhumanpy.git

If you require GPU acceleration for enhanced performance on compatible hardware, install the package with GPU dependencies:

pip install panhumanpy[gpu]

or from GitHub:

pip install git+https://github.com/satijalab/panhumanpy.git#egg=panhumanpy[gpu]

Model Versions

panhumanpy uses versioned models corresponding to major package releases. The package defaults to model 'v{i}' where i is the major package version. For example for panhumanpy 0.2.1 (Andromeda), the default model version is 'v0'. For most users, the default version is recommended. The user can also choose to use a different model version as outlined in the tutorial mentioned below.

Currently available model versions: 'v0', 'v1'

Model Weights

Model weights are hosted on Zenodo and downloaded automatically on first use, cached in ~/.cache/panhumanpy/. No manual download is required.

Field	Detail
DOI	https://doi.org/10.5281/zenodo.20401417
Models	v0, v1
License	CC BY 4.0

Cell Ontology Mapping

panhumanpy includes a built-in crosswalk that maps Pan-human Azimuth cell type annotations to Cell Ontology (CL) terms. This mapping is versioned alongside the model and can be applied to annotation outputs via the map_to_cell_ontology function in ANNotate_tools or the map_to_cell_ontology method on AzimuthNN and AzimuthNN_base.

Crosswalk provenance:

Field	Detail
Title	Crosswalk of Pan-human Azimuth Types annotated cells to Cell Ontology
Author	Aleix Puig-Barbe
Author ORCID	0000-0001-6677-8489
Reviewers	Bruce Herr II, Katy Borner, Jie Zheng
Reviewer ORCIDs	0000-0002-6703-7647, 0000-0002-3321-6137, 0000-0002-2999-0103
Data DOI	https://doi.org/10.48539/HBM727.TLKL.237
Date	December 15, 2025
Version	v1.1

Tutorial

For an introductory tutorial, please check out this notebook.