scfm is a Python library to perform molQTL fine-mapping across multiple cell types in single cell data.
Installation | Example | Notes | Version | Support | Other Software
Users can download the latest repository and then use pip:
git clone https://github.com/mancusolab/scfm.git
cd scfm
pip install .TBD
scfmuses JAX with Just In Time compilation to achieve high-speed computation. However, there are some issues for JAX with Mac M1 chip. To solve this, users need to initiate conda using miniforge, and then installscfmusingpipin the desired environment.
TBD
Please report any bugs or feature requests in the Issue Tracker. If users have any questions or comments, please contact Camellia Rui (crui@usc.edu) and Nicholas Mancuso (nmancuso@usc.edu).
Feel free to use other software developed by Mancuso Lab:
- SuShiE: a Bayesian fine-mapping framework for molecular QTL data across multiple ancestries.
- GiddyUp: a Python library to compute p-values of scores computed under exponential family models using saddlepoint approximation of the sampling distribution.
- MA-FOCUS: a Bayesian fine-mapping framework using TWAS statistics across multiple ancestries to identify the causal genes for complex traits.
- SuSiE-PCA: a scalable Bayesian variable selection technique for sparse principal component analysis
- twas_sim: a Python software to simulate TWAS statistics.
- FactorGo: a scalable variational factor analysis model that learns pleiotropic factors from GWAS summary statistics.
- HAMSTA: a Python software to estimate heritability explained by local ancestry data from admixture mapping summary statistics.
scfm is distributed under the terms of the MIT license.
This project has been set up using Hatch. For details and usage information on Hatch see https://github.com/pypa/hatch.