https://github.com/pblischak/hyde-cnn
Hybridization Detection with Convolutional Neural Networks
https://github.com/pblischak/hyde-cnn
convolutional-neural-networks deep-learning hybridization phylogenomics python3
Last synced: 6 months ago
JSON representation
Hybridization Detection with Convolutional Neural Networks
- Host: GitHub
- URL: https://github.com/pblischak/hyde-cnn
- Owner: pblischak
- License: gpl-3.0
- Created: 2019-07-13T17:54:35.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2021-01-26T21:56:56.000Z (over 4 years ago)
- Last Synced: 2025-03-24T09:46:51.082Z (7 months ago)
- Topics: convolutional-neural-networks, deep-learning, hybridization, phylogenomics, python3
- Language: Python
- Homepage: https://pblischak.github.io/hyde-cnn
- Size: 8.46 MB
- Stars: 9
- Watchers: 0
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
## HyDe-CNN: Hybridization detection with convolutional neural networks
**Citation**
Blischak, P. D., M. S. Barker, and R. N. Gutenkunst. 2020. Chromosome-scale
inference of hybrid speciation and admixture with convolutional neural networks.
*bioRxiv* doi:[]().
## [ReadTheDocs](https://pblischak.github.io/hyde-cnn)
## Requirements
Below are the Python and R packages that were used for performing the analyses
in our paper. We used Python v3.7 and R v3.6.
**Python packages:**
The `environment.yml` has all of the specifications needed to recreate the conda
environment we used for simulating, training, and testing HyDe-CNN. If you just
want to install the essential packages, they are listed below:
- numpy
- matplotlib
- tensorflow
- sklearn
- tskit
- msprime
- pysam
**R packages:**
- tidyverse
- abcrf
- caret
- patchwork