ampir: Predict Antimicrobial Peptides

A toolkit to predict antimicrobial peptides from protein sequences on a genome-wide scale. It incorporates two support vector machine models ("precursor" and "mature") trained on publicly available antimicrobial peptide data using calculated physico-chemical and compositional sequence properties described in Meher et al. (2017) <doi:10.1038/srep42362>. In order to support genome-wide analyses, these models are designed to accept any type of protein as input and calculation of compositional properties has been optimised for high-throughput use. For details see Fingerhut et al. 2020 <doi:10.1101/2020.05.07.082412>.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: Peptides, caret (≥ 6.0.0), kernlab, Rcpp, parallel
LinkingTo: Rcpp
Suggests: testthat, knitr, rmarkdown, e1071
Published: 2020-05-11
Author: Legana Fingerhut ORCID iD [aut, cre], Ira Cooke ORCID iD [aut], Jinlong Zhang [ctb] (R/read_faa.R), Nan Xiao [ctb] (R/calc_pseudo_comp.R)
Maintainer: Legana Fingerhut <legana.fingerhut at>
License: GPL-2
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: ampir results


Reference manual: ampir.pdf
Vignettes: Introduction to ampir
How to train your model
Package source: ampir_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: ampir_1.0.0.tgz, r-oldrel: ampir_1.0.0.tgz
Old sources: ampir archive


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