person("Florent", "Angly", role = "aut"),
Imports: rex, crayon, codetools, cyclocomp, testthat (>= 2.2.1),
Collate: 'T_and_F_symbol_linter.R' 'utils.R' 'aaa.R' 'actions.R'

person("Florent", "Angly", role = "aut", comment = "fangly"),
person("Michael", "Chirico", role = "aut"),
person("Alexander", "Rosenstock", role = "aut", comment = "AshesITR")
Description: Checks adherence to a given style, syntax errors and possible semantic issues.
Supports on the fly checking of R code edited with 'RStudio IDE', 'Emacs', 'Vim', 'Sublime Text',
Imports: rex, crayon, codetools, cyclocomp, digest, glue, jsonlite,
knitr, stats, utils, xml2 (>= 1.0.0), xmlparsedata (>= 1.0.3),
Suggests: covr, httr (>= 1.2.1), mockery, patrick, pkgdown, rmarkdown,
rstudioapi (>= 0.2), testthat (>= 3.0.0), tibble, withr
Packaged: 2022-06-13 15:49:09 UTC; jimhester

person("Jim", "Hester", , "james.f.hester@gmail.com", role = c("aut", "cre")),
person("Florent", "Angly", role = "aut",
person("Alexander", "Rosenstock", role = "aut",
person("Indrajeet", "Patil", role = "aut", email = "patilindrajeet.science@gmail.com",
semantic issues.  Supports on the fly checking of R code edited with
'RStudio IDE', 'Emacs', 'Vim', 'Sublime Text', 'Atom' and 'Visual
Imports: backports, codetools, crayon, cyclocomp, digest, glue,
jsonlite, knitr, rex, stats, utils, xml2 (>= 1.0.0),
rstudioapi (>= 0.2), testthat (>= 3.0.0), tibble, withr (>=
Packaged: 2022-09-09 18:21:48 UTC; jimhester

Packaged: 2022-10-11 19:02:22 UTC; jimhester

Description: Lipid Maps Rest service. Researchers can access the Lipid Maps Rest
service programmatically and conveniently integrate it into the current workflow

Title: Integrative Visualizations of the Lipidome
Authors@R: c( person( "Tommi", "Suvitaival",
Description: Create lipidome-wide heatmaps of statistics with the 'lipidomeR'.
The 'lipidomeR' provides a streamlined pipeline for the systematic
interpretation of the lipidome through publication-ready visualizations
of regression models fitted on lipidomics data.
With 'lipidomeR', associations between covariates and the lipidome
can be interpreted systematically and intuitively through heatmaps, where
lipids are categorized by the lipid class and are presented on
two-dimensional maps organized by the lipid size and level of saturation.
This way, the 'lipidomeR' helps you gain an immediate understanding of
the multivariate patterns in the lipidome already at first glance.
You can create lipidome-wide heatmaps of statistical associations, changes,
differences, variation, or other lipid-specific values.
The heatmaps are provided with publication-ready quality and the results
behind the visualizations are based on rigorous statistical models.
Imports: BiocManager, dplyr, ggplot2, knitr, limma, reshape2,
Author: Tommi Suvitaival [aut, cre] (<https://orcid.org/0000-0002-2583-4912>)