## Biostatistics analysis of RNA-Seq data

This course is part of the INRAE training session about “bioinformatics and biostatistics analysis of RNA-seq data” and of the Biostatistics platform “Initiation à LA statistique, niveau 4”. The previous sessions were held in Toulouse on November 18-21, 2014, April 2-3, 2015, September 23-24, 2015, May 18-19, 2017, February 11-12, 2019, and November 4-5, 2020. The next session is scheduled on April 14th, 2021 (videoconference session)

The material provided on the present webpage is related to the biostatistics part and covers the following topics:

• R and RStudio
• design of experiments
• variability
• count data normalization
• differential analysis

The material has been prepared by Ignacio Gonzales, Annick Moisan and myself. The class has already been taught by these persons but also by Gaëlle Lefort and Jérôme Mariette.

Pre-requisites: A background in R programming is necessary for this class. Before the class, please download the course material and install R, RStudio and the packages as described below. To produce high quality figures, I will use ggplot2 for plots but will not enter into details about the ggplot2 syntax. If you are not familiar with it, you can just use these command lines or switch to base plots instead. Do not hesitate to contact me before the class if you have any difficulty to install one of these packages!

## Required installation for the practical application

R is needed for the practical application and RStudio is strongly advised. If possible, use R version 4.0 or higher. Detailed installation instructions are provided on this page.

### CRAN packages

• ggplot2
• gridExtra
• reshape2
• RColorBrewer
• VennDiagram
• devtools

These packages can be installed using the following command line in an R console:

(and similarly for the other packages).

### Bioconductor packages

• mixOmics
• edgeR

These packages can be installed using the following command lines in an R console (after the CRAN package BiocManager has been installed as above with the install.packages function):

(and similarly for the other packages).

The precise versions of R and of the packages used in the practical application are given at the end (“Session information” section) of the solution of the analysis (this HTML file).