unix, KernSmooth, KEGGREST, survival, ctc, knitr, rmarkdown

Suggests: glpkAPI (>= 1.3.0), topGO (>= 2.24.0), unix, KEGGREST,

Title: Datasets and Functions for Reproducing Meta-Analyses
Description: Dataset and functions from the meta-analysis published in Medicine & Science in Sports & Exercise.
It contains all the data and functions to reproduce the analysis.
"Effectiveness of HIIE versus MICT in Improving Cardiometabolic Risk Factors in Health and Disease: A Meta-analysis".
Felipe Mattioni Maturana, Peter Martus, Stephan Zipfel, Andreas M Nieß (2020) <doi:10.1249/MSS.0000000000002506>.
Imports: tibble, magrittr, usethis, dplyr (>= 1.0.0), ggplot2 (>=
3.2.1), ggfittext, cli (>= 2.0.1), forcats, ggimage, patchwork
(>= 1.0.0), scales, stringr, tidyr (>= 1.0.2), purrr, meta (>=
Suggests: knitr, here, Rd2roxygen, kableExtra, fansi, downloadthis (>=
Packaged: 2020-09-23 21:07:25 UTC; fmattioni
Author: Felipe Mattioni Maturana [aut, cre, cph]

Packaged: 2022-09-09 06:36:46 UTC; fmattioni

Title: Interface to the 'Metabolights' RESTful API
Description: Access to the 'Metabolights' RESTful API <https://www.ebi.ac.uk/metabolights/index>. Retrieve elements of publically available 'Metabolights' studies.
Author: Tom Wilson [aut, cre] (<https://orcid.org/0000-0003-3112-4682>)

Suggests: covr, testthat, tibble, knitr, rmarkdown, tidyr

Title: Interface to the 'Metabolights' REST API
Description: Access to the 'Metabolights' REST API <https://www.ebi.ac.uk/metabolights/index>. Retrieve elements of publicly available 'Metabolights' studies.

Title: A collection of functions for analysing metabolomics data
Author: Alysha M De Livera and Jairus B Bowne
Description: A collection of functions to aid in the statistical

Description: A collection of functions to aid in the statistical analysis of metabolomic data

Depends: limma, crmn, gplots, R (>= 3.1.0)

Description: Tools to preprocess, analyse, and visualize metabolomics data.
We included a set of functions for sample and metabolite quality control,
outlier detection, missing value imputation, dimensional reduction, normalization,
data integration, regression, metabolite annotation, enrichment analysis,
and visualization of data and results. The package is designed to be a comprehensive R package
that can be easily used by researchers with basic R programming skills.
The framework designed here is versatile and is extensible to other various methods.
Imports: ggplot2, data.table, plotROC, utils, stats
Suggests: ggthemes, knitr, rmarkdown, testthat (>= 3.0.0), lme4, nlme,
broom, reshape2, impute, M3C, FNN, RColorBrewer, readxl,
survival, future, pbapply, future.apply, progressr, ggrepel,
here, genuMet, ggstatsplot, cowplot, pROC, BiocStyle, MASS,
biocViews: Software, Metabolomics, MassSpectrometry, Regression,