From the 30th November - 2nd December, five bioinformaticians from the Walter and Eliza Hall Institute for Medical Research will be visiting Nanjing University to provide a series of training workshops on bioinformatics methods to analyse different kinds of data. This is an exciting opportunity for staff and students of the university to learn about bioinformatics analysis methods from experienced researchers with many years of experience in the analysis of data and the development of analysis methods.
RNA-Sequencing Analysis Workshop
In this workshop, you will be learning how to analyse RNA-seq count data using R. This will include reading the data into R, pre-processing data and performing differential expression analysis, with a focus on the limma-voom analysis workflow. You will learn how to generate common plots for analysis and visualisation of gene expression data, such as boxplots and heatmaps.
This workshop is aimed at biologists interested in learning how to perform differential expression analysis of RNA-seq data when reference genomes are available. The material we will be covering on RNA-seq is available at .
The course is aimed at PhD students, Master's students, and third & fourth year undergraduate students. Some basic R knowledge is assumed - this is not an introduction to R course. If you are not familiar with the R statistical programming language it is compulsory that you work through an introductory R course before you attend this workshop - the Software Carpentry lessons up to and including vectorisation (topic 9) is recommended.
Single-Cell RNA-Sequencing Analysis Workshop
In this workshop, you will be learning how to analyse single-cell RNA-sequencing count data produced by the Chromium 10x platform using R. This will include reading the data into R, pre-processing data, normalization, feature selection, dimensional reduction and downstream analysis such as clustering and cell type annotation. You will learn how to generate common plots for analysis and visualisation of single cell gene expression data, such as diagnostic plots to assess the data quality as well as dimensionality reduction techniques such as principal components analysis and t-distributed stochastic neighbourhood embedding (t-SNE). The material we will be covering on RNA-seq is available at .
Preparations
For RNA-seq Workshop
Download R and RStudio
Open RStudio as Administor, Select tools-global options-packages-CRAN mirror-change-China (Beijing) [https] - TUNA Team, Tsinghua University
Create and set working directory: Select tools-global options-general-default working directory (Note: chinese characters is not allowed)
Install R packages (Note: update all the packages when installing)
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("RNAseq123")
Check your packages and files (Note: This will produce output even if everything has worked. Please read the output carefully to make sure there are no 'error' or 'warning' messages)