Episode 17: Tidal Waves of R Packages

In this episode, I pared down three important -omics data considerations, coded my way into wave of new R packages, boasted about the Big Book of R, and havered over the ‘dots’ package. References: Editorial: Statistical Data Science - Theory and Applications in Analyzing Omics Data Introducing riskCommunicator: An R package to obtain interpretable effect estimates for public health On the mixed Kibria–Lukman estimator for the linear regression model Rejection Region (Critical Region) for Statistical Tests Join rstudio::conf(2022) Virtually ggdensity: A new R package for plotting high-density regions R Color Generalized Linear Models, Part I: The Logistic Model Part 1 of 3: 300+ milestone for Big Book of R Part 2 of 3: 300+ milestone for Big Book of R Part 3 of 3: 300+ milestone for Big Book of R R-packages: htmcglm:  Hypothesis Testing for McGLMs nextGenShinyApps:  Advanced Tools for Building the Next Generation of 'Shiny' Applications and Dashboards robustmeta:  Robust Inference for Meta-Analysis with Influential Outlying Studies lnmCluster:  Perform Logistic Normal Multinomial Clustering for Microbiome Compositional Data binaryTimeSeries:  Analyzes a Binary Variable During a Time Series codebookr:  Create Codebooks from Data Frames dots:  Dot Density Maps ggpackets:  Package Plot Layers for Easier Portability and Modularization trouBBlme4SolveR:  Troubles Solver for 'lme4'