deepredeff: Deep Learning Prediction of Effectors

A tool that contains trained deep learning models for predicting effector proteins. 'deepredeff' has been trained to identify effector proteins using a set of known experimentally validated effectors from either bacteria, fungi, or oomycetes. Documentation is available via several vignettes, and the paper by Kristianingsih and MacLean (2020) <doi:10.1101/2020.07.08.193250>.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: Biostrings, dplyr, ggplot2, ggthemes, keras, magrittr, purrr, reticulate, rlang, seqinr, tensorflow
Suggests: covr, kableExtra, knitr, rmarkdown, stringr, testthat
Published: 2020-10-23
Author: Ruth Kristianingsih ORCID iD [aut, cre, cph]
Maintainer: Ruth Kristianingsih <ruth.kristianingsih30 at gmail.com>
BugReports: https://github.com/ruthkr/deepredeff/issues/
License: MIT + file LICENSE
URL: https://github.com/ruthkr/deepredeff/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: deepredeff results

Downloads:

Reference manual: deepredeff.pdf
Vignettes: overview
predict
Package source: deepredeff_0.1.0.tar.gz
Windows binaries: r-devel: deepredeff_0.1.0.zip, r-release: deepredeff_0.1.0.zip, r-oldrel: deepredeff_0.1.0.zip
macOS binaries: r-release: deepredeff_0.1.0.tgz, r-oldrel: deepredeff_0.1.0.tgz

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