Skip to main content

scmallet

Python wrapper of MALLET for LDA analysis on single-cell data.

MALLET is the LDA backend chosen by pycistopic. The implementation in this package has several difference than pycistopic:

  1. Improved paralization.
  2. Allow train LDA model with cell subset and then inference ramaining cells. This is nicely supported by MALLET itself.
  3. Allow the training process to be resumable.
  4. Work with anndata.

Installation

You need to have Python 3.9 or newer installed on your system. If you don't have Python installed, we recommend installing Mambaforge.

There are several alternative options to install scmallet:

  1. Install the latest release of scmallet from PyPI:
pip install scmallet
  1. Install the latest development version:
pip install git+https://github.com/lhqing/scmallet.git@main

Usage

See example usage here: https://github.com/lhqing/scmallet/blob/main/tests/example.ipynb

Citation

Metadata

Release files for scmallet 0.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for scmallet 0.1.2
File Size Uploaded Provenance Actions
scmallet-0.1.2.tar.gz 24.8 kB Without provenance Details for scmallet-0.1.2.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for scmallet 0.1.2
File Interpreter ABI Platform Actions
scmallet-0.1.2-py3-none-any.whl Python 3 none any Details for scmallet-0.1.2-py3-none-any.whl

Total release size: 44.7 kB

Release files / scmallet-0.1.2.tar.gz

Download URL scmallet-0.1.2.tar.gz
Size 24.8 kB
Tags Source
SHA-256 checksum
How to use checksums
5a7be27e1c542529ff651808edd704ae894e01c4a82de6102cbba28f24700284
BLAKE2b-256 checksum
How to use checksums
dd73972f1be2a7006cb4df75f5ab4fa8370537118ea85942d8be55196956acf9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.12.3

Release files / scmallet-0.1.2-py3-none-any.whl

Download URL scmallet-0.1.2-py3-none-any.whl
Size 19.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
183feecc31007631d9e6b96c30d92f716ec67fe82e365c91caa591a9393331de
BLAKE2b-256 checksum
How to use checksums
a0a745b83f94300af1b04784d3f90ec8099a9d7b6a1b6814af2c5c09c5be3ecc
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.12.3

Security for scmallet 0.1.2

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page