Heritability Estimation with high Efficiency using LD and Summary Statistics
HEELS is a Python-based command line tool that produce accurate and precise local heritability estimates using summary-level statistics (marginal association test statistics along with the empirical (in-sample) LD statistics).
You can clone the repository with the following command:
$ git clone https://github.com/huilisabrina/HEELS.git
$ cd HEELS
This should take a few seconds to finish. In order to install the Python dependencies, you will need the conda package manager or its faster implementation, Mamba. You can use the following commands to create an environment that contains the packages required by HEELS as well as their dependencies:
mamba create -n heels python=3.10.12 pip numpy pandas scipy pandas-plink joblib
source activate heels
mamba install scikit-learn-intelex -c conda-forge
To test whether installation is done properly, open a new shell or terminal, type the following commands.
conda activate heels
python ./run_HEELS.py -h
If HEELS has been installed successfully, you should see a brief description of the software and a list of the accepted command-line options. If an error occurs, then something has gone wrong during installation.
You should keep your local instance of this software up to date with the changes that are made on the github repository. To do that, simply type
$ git pull
in the HEELS directory. If your local instance is outdated, git will retrieve all changes and update the code. Otherwise, you will be told that your local instance is already up-to-date.
We are happy to answer any questions you may have about using the software. Before opening an issue, please be sure to read the wiki page and read more about our method via the link below. Please also reference the descriptions about our input flags to understand their proper usage. If your problem persists, please do the following: as the next step:
- Rerun the specification that is causing the error, being sure to specify
--verboseto generate a descriptive logfile. - Attach your log file in the issue.
You may also contact us via email, although we encourage github issues so others can benefit from your question as well.
If you are using the HEELS method or software, please cite Li, H., Mazumder, R. & Lin, X. Accurate and efficient estimation of local heritability using summary statistics and the linkage disequilibrium matrix. Nat Commun 14, 7954 (2023). doi: https://doi.org/10.1038/s41467-023-43565-9. Link to the paper here.
This package is available under the MIT license.
Hui Li (Department of Biostatistics, Harvard T.H. Chan School of Public Health)
Rahul Mazumder (Operations Research Center and Center for Statistics and Data Science, MIT Sloan School of Management)
Xihong Lin (Department of Biostatistics and Department of Statistics, Harvard University)
We are very grateful to Luke O’Connor, Huwenbo Shi, Alkes Price, Samuel Kou, Ben Neale and Shamil Sunyaev for their helpful discussions and feedback. This work was supported by grants R35-CA197449, 548U19-CA203654, R01-HL163560, U01-HG012064 and U01-HG009088 (X. Lin).