Package: fioRa 0.3.16

fioRa: Mass-Spectra Prediction Using the FIORA Model

Provides a wrapper for the python module 'FIORA' as well as a 'shiny'-App to facilitate data processing and visualization. 'FIORA' allows to predict Mass-Spectra based on the SMILES code of chemical compounds. It is described in the Nature Communications article by Nowatzky (2025) <doi:10.1038/s41467-025-57422-4>.

Authors:Jan Lisec [aut, cre]

fioRa_0.3.16.tar.gz
fioRa_0.3.16.zip(r-4.7)fioRa_0.3.16.zip(r-4.6)fioRa_0.3.16.zip(r-4.5)
fioRa_0.3.16.tgz(r-4.6-any)fioRa_0.3.16.tgz(r-4.5-any)
fioRa_0.3.16.tar.gz(r-4.7-any)fioRa_0.3.16.tar.gz(r-4.6-any)
fioRa_0.3.16.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
fioRa/json (API)

# Install 'fioRa' in R:
install.packages('fioRa', repos = c('https://janlisec.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/janlisec/fiora/issues

Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT
Datasets:
  • test_data - The example set of test compounds provided with FIORA.

On CRAN:

Conda:

openjdk

4.11 score 2 stars 166 downloads 5 exports 48 dependencies

Last updated from:da7321e276. Checks:1 ERROR, 8 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR319
source / vignettesOK217
linux-release-x86_64OK180
macos-release-arm64OK101
macos-oldrel-arm64OK134
windows-develOK212
windows-releaseOK157
windows-oldrelOK207
wasm-releaseOK133

Exports:install_fioraplot_specread_fiorarun_apprun_script

Dependencies:attemptbase64encbslibcachemclicommonmarkconfigdigestenviPatfastmapfingerprintfontawesomefsgluegolemherehtmltoolshttpuvInterpretMSSpectrumiteratorsitertoolsjquerylibjsonlitelaterlifecyclemagrittrmemoisemimeotelplyrpngpromisesR6rappdirsrcdkrcdklibsRcpprJavarlangrprojrootsassshinyshinyjssourcetoolswaiterwithrxtableyaml