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Instructor-led course

Provided by: Bioinformatics


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Analysis of RNA-seq data with Bioconductor


Description

This course provides an introduction to the tools available through the Bioconductor project for manipulating and analysing bulk RNA-seq data. We will present a workflow for the analysis RNA-seq data starting from aligned reads in bam format and producing a list of differentially-expressed genes. We will also describe the various resources available through Bioconductor to annotate, visualise and gain biological insight from the differential expression results.

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

Target audience
  • 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 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
  • Further details regarding eligibility criteria are available here
Prerequisites
  • A knowledge of current sequencing technologies, data formats (e.g. fastq and bam) and alignment
  • A very basic knowledge of UNIX would be an advantage, but nothing will be assumed and extremely little will be required
  • Attendees should be comfortable with using the R statistical language to read and manipulate data, and produce simple graphs. Here is an R crash course that we suggest looking through before attending this course.
Topics covered

Bioinformatics, Data handling, Data mining, Data visualisation, Functional genomics

Objectives

After this course you should be able to:

  • Understand the advantages and limitations of the high-throughput assays presented
  • 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
Aims

During this course you will learn about:

  • Quality assessment of raw sequencing reads and aligned reads using R
  • Sources of variation in RNA-seq data
  • Differential expression analysis using edgeR and DEseq
  • Annotation resources in Bioconductor
  • Identifying over-represented gene sets amongst a list of differentially-expressed genes
Format

Presentations and practicals

Timetable

Day 1 Topics Speaker(s)
09:30 - 10:30 Introduction to RNA-seq Ashley Sawle
10:30 - 12:30 Aligning and Counting for RNA-seq data Stephane Ballereau
12:30 - 13:30 Lunch
13:30 - 17:00  Linear Models and Statistics for Differential Expression Oscar Rueda
Day 2
9:30 - 11:00 Importing and QC of RNA-seq data Ashley Sawle
11:00 - 12:30  Differential Expression Oscar Rueda
12:30 -13:30  Lunch
13:30 - 15:00  Annotation and Visualisation of Differential Expression Mark Dunning
15:00 - 17:00 Gene set analysis and Gene Ontology testing Stephane Ballereau
Registration fees
  • Free for University of Cambridge students
  • £ 50/day for all University of Cambridge staff, including postdocs, 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
Duration

2 days

Frequency

A number of times per year

Theme
Specialized Training

Events available