sendigR: Enable Cross-Study Analysis of 'CDISC' 'SEND' Datasets

A system enables cross study Analysis by extracting and filtering study data for control animals from 'CDISC' 'SEND' Study Repository. These data types are supported: Body Weights, Laboratory test results and Microscopic findings. These database types are supported: 'SQLite' and 'Oracle'.

Version: 1.0.0
Depends: R (≥ 4.1.0)
Imports: RSQLite, data.table, readxl, magrittr, xfun, stringr, DescTools, parsedate, shiny, shinydashboard, htmltools, DT, dplyr, ggplot2, Hmisc, haven, plotly, cicerone, reticulate, sjlabelled
Suggests: knitr, rmarkdown, logr, shinycssloaders, testthat
Published: 2022-08-18
DOI: 10.32614/CRAN.package.sendigR
Author: Bo Larsen [aut], Yousuf Ali [aut], Kevin Snyder [aut], William Houser [aut], Brianna Paisley [aut], Cmsabbir Ahmed [aut], Susan Butler [aut], Michael Rosentreter [aut], Michael Denieu [aut], Wenxian Wang [cre, aut], BioCelerate [cph]
Maintainer: Wenxian Wang < at>
License: MIT + file LICENSE
NeedsCompilation: no
SystemRequirements: Python(>=3.9.6)
Materials: README
CRAN checks: sendigR results


Reference manual: sendigR.pdf
Vignettes: Introduction to sendigR
Using xptcleaner


Package source: sendigR_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): sendigR_1.0.0.tgz, r-oldrel (arm64): sendigR_1.0.0.tgz, r-release (x86_64): sendigR_1.0.0.tgz, r-oldrel (x86_64): sendigR_1.0.0.tgz


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