EastBio Primer for Advanced ‘Transcriptomics’ Approaches

Facilitator name: Dr Runxuan Zhang (The James Hutton Institute, Information and computational sciences department)

Participant cap: 20

Contact details: Runxuan.zhang@hutton.ac.uk

The course focused on RNA-seq data from mixed cell populations (bulk RNA-seq) rather than single cell data. The course is suitable for someone who is new to RNA-seq analysis with no coding skills required. Basic knowledge of applied statistics and molecular biology is assumed although extra reading is provided for students who need to refresh their knowledge of these subjects. In this course, we will use Galaxy (https://usegalaxy.eu/) and 3D RNA-seq (https://3drnaseq.hutton.ac.uk) to carry out advanced gene expression and transcriptomics analysis, including quantifications, differential gene expression (DE) and alternative splicing (DAS) analyses.

The course will cover the skills necessary to analyse and interpret RNA-seq data. The typical student on the course may be interested in using skills gained on the course for analysis of data available online or analysing and interpreting their own lab data. The tools used in this course have user friendly graphical interfaces and are highly interactive. PhD students will develop their understanding of statistics and RNA-seq data through exploring of sample data or their own data. We make several data sets available on different species (e.g. Arabidopsis and mouse). The skills taught are directly applicable to other biological domains.

Learning Outcomes:

At the end of the course students will:

• develop a good understanding of the state of art methods on RNA-seq data analysis.
• be able to perform an RNA-seq analysis and interpret the analysis outcomes.
• Be able to apply the skills learned in this course to guide their experimental design and carry out RNA-seq data from their own projects.

Recommended reading:

This is quite an accessible review for basic molecular biology
https://www.sciencedirect.com/science/article/pii/B9780080918655000035?via%3Dihub

This is a good RNA-seq review
https://www.annualreviews.org/doi/abs/10.1146/annurev-biodatasci-072018-021255

A paper helps to understand the challenges and methods for transcript level analysis and alternative splicing

https://academic.oup.com/nar/article/45/9/5061/3603319

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02711-0

Two computational tools on transcript level quantification

https://www.nature.com/articles/nbt.3519

https://www.nature.com/articles/nmeth.4197

Detailed methods in 3D RNA-seq

https://www.tandfonline.com/doi/full/10.1080/15476286.2020.1858253

3D RNA-seq user manual and tutorial video

https://github.com/wyguo/ThreeDRNAseq/blob/master/vignettes/user_manuals/3D_RNA-seq_App_manual.md

If you have further questions, please email enquiries@eastscotbiodtp.ac.uk.

Please note the cancellation policy on the EastBio Website.