LongDat: A Tool for 'Confounder'-Sensitive Longitudinal Analysis on 'Multi-omics' Data

This tool takes longitudinal dataset as input and analyzes if there is significant change of the features over time (a proxy for treatments), while detects and controls for 'confounders' simultaneously. 'LongDat' is able to take in several data types as input, including count, proportion, binary, ordinal and continuous data. The output table contains p values, effect sizes and 'confounders' of each feature, making the downstream analysis easy.

Version: 1.0.3
Depends: R (≥ 4.0.0)
Imports: lme4, reshape2, glmmTMB, emmeans, bestNormalize, MASS, ggplot2, stringr, magrittr, tibble, dplyr, graphics, utils, stats, rlang, car, rstatix, effsize, tidyr, patchwork
Suggests: rmarkdown, knitr, tidyverse, kableExtra
Published: 2022-02-26
Author: Chia-Yu Chen ORCID iD [aut, cre], Sofia Forslund ORCID iD [ctb]
Maintainer: Chia-Yu Chen <Chia-Yu.Chen at mdc-berlin.de>
BugReports: https://github.com/CCY-dev/LongDat/issues
License: GPL-2
URL: https://github.com/CCY-dev/LongDat
NeedsCompilation: no
Language: en-US
Citation: LongDat citation info
Materials: README NEWS
CRAN checks: LongDat results


Reference manual: LongDat.pdf
Vignettes: longdat_cont_tutorial


Package source: LongDat_1.0.3.tar.gz
Windows binaries: r-devel: LongDat_1.0.3.zip, r-release: LongDat_1.0.3.zip, r-oldrel: LongDat_1.0.3.zip
macOS binaries: r-release (arm64): LongDat_1.0.3.tgz, r-oldrel (arm64): LongDat_1.0.3.tgz, r-release (x86_64): LongDat_1.0.3.tgz, r-oldrel (x86_64): LongDat_1.0.3.tgz
Old sources: LongDat archive


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