varDFE

Current version: 0.1.0 Last updated: 2024-10-16

Folder structure

.
├── README.md
├── dfe.yml # yaml file for creating the conda environment
├── src # contents of the varDFE package
│   └── varDFE
│       ├── DFE
│       │   ├── Cache1D_mod2.py
│       │   ├── Cache1D_util.py
│       │   ├── DFEGridsearchWorker.py
│       │   ├── DFEInferenceWorker.py
│       │   ├── DemogSelModels2.py
│       │   ├── InputDFE.py
│       │   ├── OutputDFE.py
│       │   ├── PDFValidation.py
│       │   ├── PDFs2.py
│       │   └── __init__.py
│       ├── Demography
│       │   ├── DemogValidation.py
│       │   ├── Demographics1D2.py
│       │   ├── InputDemog.py
│       │   ├── OutputDemog.py
│       │   └── __init__.py
│       ├── Misc
│       │   ├── LoggerDFE.py
│       │   ├── Plotting.py
│       │   ├── Util.py
│       │   └── __init__.py
│       └── __init__.py
├── workflow # python API for running the workflows
│   ├── DFE
│   │   ├── DFE1D_gridsearch.py
│   │   ├── DFE1D_inferenceFIM.py
|   │   └── DFE1D_refspectra.py
|   └── Demography
|       └── Demog1D_sizechangeFIM.py
├── example # example folder for running the workflows
│   ├── MIS.sfs
│   ├── SYN.sfs
│   ├── varDFE.ipynb
│   └── output # output folder from varDFE.ipynb (not included)
├── pyproject.toml
└── setup.cfg

Features

1. provide quick and easy demographic inference workflow for simple size change models.
2. pre-compute the DFE spectra given the inferred demographic model.
3. perform quick and parallel DFE inference for various DFE functional forms.
4. compare DFE inferred in different populations using a gridsearch approach.

Installation

We recommend using varDFE in a conda environment as an editable package.

1. install miniconda3
2. set up the conda environment dfe and install the required packages listed in dfe.yml
3. install varDFE as an editable package

# Please ensure that miniconda3 is installed before executing the following commands

# download varDFE
wget https://github.com/meixilin/varDFE/archive/refs/heads/master.zip

# unzip varDFE into your working directory
cd <your-dir>
unzip master.zip
mv varDFE-master varDFE
cd varDFE
# yaml file for creating the conda environment should be available
ls dfe.yml

# create the conda environment `dfe`
conda env create -f dfe.yml
conda activate dfe
which pip
# should be: <your-dir>/miniconda3/envs/dfe/bin/pip
pip install -e ./

Documentation and tutorials

Tutorial on inferring the DFE from a Site-Frequency Spectrum (SFS) using varDFE is available in the example folder.

License

varDFE is released under the GNU General Public License v3.0 license.

Disclaimer: varDFE and this tutorial is provided "as is" without any warranties or representations of any kind, express or implied. I make no guarantees or warranties regarding the accuracy, reliability, completeness, suitability, or timeliness of the software.

Citation

If you use varDFE in your research, please cite our paper:

[Upcoming information]

Remember to cite the dadi package and fitdadi this package is based on as well.

RN Gutenkunst, RD Hernandez, SH Williamson, CD Bustamante "Inferring the joint demographic history of multiple populations from multidimensional SNP data" PLoS Genetics 5:e1000695 (2009).

BY Kim, CD Huber, KE Lohmueller "Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples" Genetics 206:345 (2017).

Contact

For questions and support, please open an issue on GitHub.