R Packages

ggpubr: ggplot2’ Based Publication Ready Plots

ggplot2 by Hadley Wickham is an excellent and flexible package for elegant data visualization in R. However the default generated plots requires some formatting before we can send them for publication. Furthermore, to customize a ggplot, the syntax is opaque and this raises the level of difficulty for researchers with no advanced R programming skills.

The ‘ggpubr’ package provides some easy-to-use functions for creating and customizing ‘ggplot2’- based publication ready plots.

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factoextra : Extract and Visualize the Results of Multivariate Data Analyses

Provides some easy-to-use functions to extract and visualize the output of multivariate data analyses, including:

• PCA: Principal Component Analysis,
• CA: Correspondence Analysis
• MCA: Multiple Correspondence Analysis
• FAMD: Factor Analysis of Mixed Data
• MFA: Multiple Factor Analysis
• HMFA: Hierarchical Multiple Factor Analysis.

It contains also functions for simplifying some clustering analysis steps and provides ‘ggplot2’ - based elegant data visualization.

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survminer: Drawing Survival Curves using ggplot2

Contains the function ggsurvplot()‘for drawing easily beautiful and ’ready-to-publish’ survival curves with the ‘number at risk’ table and ‘censoring count plot’. Other functions are also available to plot adjusted curves for Cox model and to visually examine ‘Cox’ model assumptions.

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ggcorrplot: Visualization of a Correlation Matrix using GGPlot2

The ggcorrplot package can be used to visualize easily a correlation matrix using ggplot2. It provides a solution for reordering the correlation matrix and displays the significance level on the correlogram. It includes also a function for computing a matrix of correlation p-values.

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rstatix: Pipe-friendly Framework for Basic Statistical Tests in R

Provides a pipe-friendly framework to perform easily basic statistical tests in R. The output of each test is automatically transformed into a tidy data frame to facilitate visualization.

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fastqcr: Quality Control of Sequencing Data

FASTQC is the most widely used tool for evaluating the quality of high throughput sequencing data. It produces, for each sample, an html report and a compressed file containing the raw data.

If you have hundreds of samples, you are not going to open up each ‘HTML’ page. You need some way of looking at these data in aggregate.

fastqcr Provides helper functions to easily parse, aggregate and analyze FastQC reports for large numbers of samples. It provides a convenient solution for building a ‘Multi-QC’ report, as well as, a ‘one-sample’ report with result interpretations.

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datarium: Data bank for statistical analyses and visualization

Contains data organized by topics: categorical data, regression model, means comparisons, independent and repeated measures ANOVA, mixed ANOVA and ANCOVA.

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