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DESCRIPTION
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DESCRIPTION
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Package: DeepGenomeScan
Type: Package
Title: DeepGenomeScan: A Deep Learning Approach for Whole Genome Scan (WGS) and Genome-wide Association Studies (GWAS)
Version: 0.5.5
Author: Xinghu Qin
Maintainer: Xinghu Qin <qinxinghu@gmail.com>
Description: 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.
License: Copyright (c 2020-2050 Xinghu Qin); GPL (>= 3)
Encoding: UTF-8
LazyData: true
SystemRequirements: GNU make
URL: https://github.com/xinghuq/DeepGenomeScan
BugReports: https://github.com/xinghuq/DeepGenomeScan/issues
biocViews:
Imports: DA,KLFDAPC,caret,robust,qvalue,NeuralNetTools
VignetteBuilder: knitr
NeedsCompilation: no
RoxygenNote: 6.1.1
Suggests: knitr,testthat,rmarkdown