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R Bioinformatics Cookbook - Second Edition

You're reading from  R Bioinformatics Cookbook - Second Edition

Product type Book
Published in Oct 2023
Publisher Packt
ISBN-13 9781837634279
Pages 396 pages
Edition 2nd Edition
Languages
Author (1):
Dan MacLean Dan MacLean
Profile icon Dan MacLean
Toc

Table of Contents (16) Chapters close

Preface 1. Chapter 1: Setting Up Your R Bioinformatics Working Environment 2. Chapter 2: Loading, Tidying, and Cleaning Data in the tidyverse 3. Chapter 3: ggplot2 and Extensions for Publication Quality Plots 4. Chapter 4: Using Quarto to Make Data-Rich Reports, Presentations, and Websites 5. Chapter 5: Easily Performing Statistical Tests Using Linear Models 6. Chapter 6: Performing Quantitative RNA-seq 7. Chapter 7: Finding Genetic Variants with HTS Data 8. Chapter 8: Searching Gene and Protein Sequences for Domains and Motifs 9. Chapter 9: Phylogenetic Analysis and Visualization 10. Chapter 10: Analyzing Gene Annotations 11. Chapter 11: Machine Learning with mlr3 12. Chapter 12: Functional Programming with purrr and base R 13. Chapter 13: Turbo-Charging Development in R with ChatGPT 14. Index 15. Other Books You May Enjoy

Using linear models and ANOVA to compare multiple groups in multiple variables

Two-way ANOVA is a statistical method used to analyze the effects of two categorical independent variables, also known as factors, on a continuous dependent variable. The two independent variables can be either fixed or random.

The main purpose of two-way ANOVA is to examine whether there is a significant interaction between the two independent variables, as well as to determine the main effects of each independent variable on the dependent variable.

The analysis involves calculating the sum of squares for each of the effects and the interaction and comparing these values to their respective degrees of freedom to obtain F ratios. The F ratios are then compared to critical values from an F-distribution to determine whether the effects are statistically significant.

Like the one-way ANOVA seen in the Using a linear model and ANOVA to compare multiple groups in a single variable recipe, the basis is...

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