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: 0.1.1
Depends: R (≥ 2.10)
Imports: Biostrings, dplyr, ggplot2, ggthemes, keras, magrittr, purrr, reticulate, rlang, seqinr, tensorflow
Suggests: covr, kableExtra, knitr, rmarkdown, stringr, testthat
Published: 2021-07-16
DOI: 10.32614/CRAN.package.deepredeff
Author: Ruth Kristianingsih ORCID iD [aut, cre, cph]
Maintainer: Ruth Kristianingsih <ruth.kristianingsih30 at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: deepredeff results


Reference manual: deepredeff.pdf
Vignettes: overview


Package source: deepredeff_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): deepredeff_0.1.1.tgz, r-oldrel (arm64): deepredeff_0.1.1.tgz, r-release (x86_64): deepredeff_0.1.1.tgz, r-oldrel (x86_64): deepredeff_0.1.1.tgz
Old sources: deepredeff archive


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