Analysis of bulk RNA-seq data (IN PERSON)

Prerequisites

PLEASE BE AWARE: This event is run in-person, if you wish to book for the online version, please click here.

The aim of this course is to familiarize the participants with the primary analysis of RNA-seq data.

This course starts with a brief introduction to RNA-seq and discusses quality control issues. Next, we will present the alignment step, quantification of expression and differential expression analysis. For downstream analysis we will focus on tools available through the Bioconductor project for manipulating and analysing bulk RNA-seq.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

• Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
• Please be aware that these courses are only free for registered University of Cambridge students. All other participants will be charged a registration fee in some form. Registration fees and further details regarding the charging policy are available here.
• After you have booked a place, if you are unable to attend any of the live sessions and would like to work in your own time, please email the Bioinfo Team as Attendance will be taken on all courses. A charge is applied for non-attendance, including for registered university students.
• Further details regarding eligibility criteria are available here

• A working knowledge of the Unix Command Line. If you do not meet this requirement, please attend our Introduction to UNIX course or revise the course materials (up to section 6).
• A working knowledge of R and RStudio. If you do not meet this requirement, please attend our Introduction to R course or revise our course materials.

Number of sessions: 3

Bioinformatics, Functional genomics, Data visualisation, Transcriptomics, Data handing, Data mining, RNA-seq

After this course you should be able to:

• Design your RNA-Seq experiments properly, considering advantages and limitations of RNA-seq assays
• Assess the quality of your datasets
• Perform alignment and quantification of expression through different tools and pipelines
• Know what tools are available in Bioconductor for RNA-seq data analysis and understand the basic object types that are utilised
• Produce a list of differentially expressed genes from an RNA-seq experiment

During this course you will learn about:

• RNA sequencing technology and considerations on experimental design
• Quality control of raw and aligned sequencing reads: FASTQC and Picard
• Read alignment to a reference genome: Hisat2
• Extract information from SAM/BAM files: samtools
• Sources of variation in RNA-seq data
• Differential expression analysis usingDEseq
• Annotation resources in Bioconductor
• Identifying over-represented gene sets among a list of differentially expressed genes

Presentations, demonstrations and practicals

• Free for registered University of Cambridge students
• £ 50/day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 50/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 100/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

3

Several times per year

• Introduction to working with UNIX and bash (IN PERSON)
• Introduction to R for Biologists (IN PERSON)
• Analysis of single cell RNA-seq data (IN PERSON)
• High Performance Computing: An Introduction (ONLINE LIVE TRAINING)
• Analysis of DNA Methylation using Sequencing (ONLINE LIVE TRAINING)