A Tool for 'Covariate'-Sensitive Longitudinal Analysis on 'omics' Data R package LongDat version 1.1.3 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 'covariates' 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 'covariates' of each feature, making the downstream analysis easy. Software 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, kableExtra Chia-Yu Chen <Chia-Yu.Chen@mdc-berlin.de> Comprehensive R Archive Network (CRAN) Chia-Yu Chen [aut, cre] (ORCID: <https://orcid.org/0000-0003-1765-7132>), Sofia Forslund [ctb] (ORCID: <https://orcid.org/0000-0003-4285-6993>) GPL-2 2024-11-19 application/tgz https://CRAN.R-project.org/package=LongDat doi:10.32614/CRAN.package.LongDat en-US