xinghuq/DeepGenomeScan: DeepGenomeScan: A Deep Learning Approach for Whole Genome Scan (WGS) and Genome-wide Association Studies (GWAS)

This package implements the whole genome scan and genome-wide association studies using deep neural networks (i.e, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN)). DeepGenomeScan offers heuristic learning and computational design integrating deep learning, robust resampling and cross validations methods, as well as Model-Agnostic interpretation of feature importance for convolutional neural networks. DeepGenomeScan, in other words, deep learning for genome-wide scanning, is a deep learning approach for detecting variations under natural selection or omics-based association studies, such as GWAS, PWAS, TWAS, MWAS. The framework makes the implemention user-friendly. Users can adopt the package's framework to study various ecological and evolutionary questions.

install.packages("remotes")
remotes::install_github("xinghuq/DeepGenomeScan")