dadi-cli
dadi-cli provides a robust and user-friendly command line interface for dadi1 to help users to quickly apply dadi to their research. dadi is a flexible python package for inferring demographic history and the distribution of fitness effects (DFE) from population genomic data. However, using dadi requires knowledge of python and patience to tune different models.
Requirements
dadi-cli works on UNIX/LINUX operating systems and tested with the following:
- Python 3.9 and 3.10
- Python packages:
- cuda
- cyvcf2
- dadi > 2.1.0
- demes
- dill
- matplotlib
- ndcctools
- nlopt
- numpy
- pycuda
- scipy
- scikit-cuda
Only NVIDIA GPUs are supported if users want to accelerate their inference with GPUs.
Installation
Users can install dadi-cli through conda-forge:
conda install -c conda-forge dadi-cli
Or, for the latest updates, clone this repo and using the following command
pip install .
Users can also use conda to create a virtual environment and install the latest dadi-cli with these two conda environment files conda-cpu-env.yml and conda-gpu-env.yml in this repo. To install conda, please follow the instruction. We recommend users install and use mamba via mambaforge or miniforge to create the virtual environment, because mamba is much faster than conda. Then users can use the following commands:
mamba env create -f conda-cpu-env.yml
mamba activate dadi-cli-cpu
To get help information, users can use
dadi-cli -h
There are fourteen subcommands in dadi-cli:
| Command | Description |
|---|---|
| GenerateFs | Generate frequency spectrum from VCF files. |
| GenerateCache | Generate selection coefficient cache for inferring DFE. |
| SimulateDM | Generate frequency spectrum based on a demographic history. |
| SimulateDFE | Generate frequency spectrum based on a DFE. |
| SimulateDemes | Generate frequency spectrum based on a Demes .yml file. |
| InferDM | Infer a demographic models from an allele frequency spectrum. |
| InferDFE | Infer distribution of fitness effects from frequency spectrum. |
| Plot | Plot 1D/2D/3D frequency spectrum. |
| StatDM | Perform statistical tests using Godambe Information Matrix for demographic models. |
| StatDFE | Perform statistical tests using Godambe Information Matrix for DFEs. |
| BestFit | Obtain the best fit parameters. |
| Model | Display available demographic models. |
| Display available probability density functions for distribution of fitness effects. | |
| ======= | |
| - GenerateFs | |
| - GenerateCache | |
| - InferDM | |
| - InferDFE | |
| - LowPass | |
| - BestFit | |
| - StatDM | |
| - StatDFE | |
| - Plot | |
| - SimulateDM | |
| - SimulateDFE | |
| - SimulateDemes | |
| - Model | |
To display help information for each subcommand, users can use the -h option. For example,
dadi-cli GenerateFs -h
In this manual, we use the data from the 1000 Genomes Project and data simulated with dadi-cli to demonstrate how to apply dadi-cli in research. Users could also refer to the dadi manual for more details on parameters in dadi.
Overview
The overview of the workflow implemented in dadi-cli is shown below:
If you need further help, you can submit questions about usage to the dadi-user Google Group.
If you've found an apparent bug or want to suggest a feature, please open an Issue.