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# Load required R packages library(ggpubr) library(rstatix) # Data preparation df <- tibble::tribble( ~sample_type, ~expression, ~cancer_type, ~gene, "cancer", 25.8, "Lung", "Gene1", "cancer", 25.5, "Liver", "Gene1", "cancer", 22.4, "Liver", "Gene1", "cancer",

# Load required R packages library(ggpubr) library(rstatix) # Data preparation df <- tibble::tribble( ~sample_type, ~expression, ~cancer_type, ~gene, "cancer", 25.8, "Lung", "Gene1", "cancer", 25.5, "Liver", "Gene1", "cancer", 22.4, "Liver", "Gene1", "cancer",

This article describes how to publish a reproducible example from R to the datanovia website using the pubr package. The goal of pubr R package is to convert reproducible R

Publish Reproducible Examples from R to Datanovia Website

This article describes how to publish a reproducible example from R to the datanovia website using the pubr package. The goal of pubr R package is to convert reproducible R

Requirements: dplyr v>=1.0.0 library(dplyr) # Data preparation df <- tibble(w = 0:2, x = 1:3, y = c("a", "b", "c"), z = c("d", "e", "f")) df ## # A tibble:

dplyr: How to Change the Order of Columns in Data Frame

Requirements: dplyr v>=1.0.0 library(dplyr) # Data preparation df <- tibble(w = 0:2, x = 1:3, y = c("a", "b", "c"), z = c("d", "e", "f")) df ## # A tibble:

Requirements: dplyr v>=1.0.0 library(dplyr) # Data preparation df <- as_tibble(iris) df ## # A tibble: 150 x 5 ## Sepal.Length Sepal.Width Petal.Length Petal.Width Species ## <dbl> <dbl> <dbl> <dbl> <fct>

dplyr: How to Select a Character Vector of Variable Names

Requirements: dplyr v>=1.0.0 library(dplyr) # Data preparation df <- as_tibble(iris) df ## # A tibble: 150 x 5 ## Sepal.Length Sepal.Width Petal.Length Petal.Width Species ## <dbl> <dbl> <dbl> <dbl> <fct>

This article describes how to compute summary statistics, such as mean, sd, quantiles, across multiple numeric columns. Key R functions and packages The dplyr package is required. We’ll

dplyr: How to Compute Summary Statistics Across Multiple Columns

This article describes how to compute summary statistics, such as mean, sd, quantiles, across multiple numeric columns. Key R functions and packages The dplyr package is required. We’ll

You will learn how to create beautiful plots in R and add summary summary statistics table such as sample size (n), median, mean and IQR onto the plot. We will

How to Create a Beautiful Plots in R with Summary Statistics Labels

You will learn how to create beautiful plots in R and add summary summary statistics table such as sample size (n), median, mean and IQR onto the plot. We will

R codes are provided for creating a nice box and whisker plot in R with summary table under the plot. # Load required R packages library(ggpubr) # Data preparation df

How to Create a Nice Box and Whisker Plot in R

R codes are provided for creating a nice box and whisker plot in R with summary table under the plot. # Load required R packages library(ggpubr) # Data preparation df

# Load required R packages suppressPackageStartupMessages(library(ggpubr)) suppressPackageStartupMessages(library(dplyr)) # Example of data from statistical tests stat.test <- tibble::tribble( ~supp, ~group1, ~group2, ~p.adj, ~p.signif, "VC", "0.5", "1", 3.4e-06, "****", "VC", "0.5", "2",

How to Draw a Textual Table with GGPLOT and Color Cells Conditionally

# Load required R packages suppressPackageStartupMessages(library(ggpubr)) suppressPackageStartupMessages(library(dplyr)) # Example of data from statistical tests stat.test <- tibble::tribble( ~supp, ~group1, ~group2, ~p.adj, ~p.signif, "VC", "0.5", "1", 3.4e-06, "****", "VC", "0.5", "2",

This article how to visualize distribution in R using density ridgeline. The density ridgeline plot is an alternative to the standard geom_density() function that can

Elegant Visualization of Density Distribution in R Using Ridgeline

This article how to visualize distribution in R using density ridgeline. The density ridgeline plot is an alternative to the standard geom_density() function that can

Prerequisites # Load required R packages library(tidyverse) library(rstatix) library(ggpubr) Data preparation We’ll use the anxiety dataset , which contains the anxiety score, measured at three time points

How to Perform Multiple Paired T-tests in R

Prerequisites # Load required R packages library(tidyverse) library(rstatix) library(ggpubr) Data preparation We’ll use the anxiety dataset , which contains the anxiety score, measured at three time points