Section outline

  • RNA-seq: From quality control to pathway analysis

    Bern, 15-16 February 2016

    Trainers: Walid Gharib, Geoffrey Fucile, Irene Keller
    Venue: University of Bern
    ECTS: 0.5 (given a passed exam at the end of the course)
    Fee: 100 CHF for academics. Others, please contact us
    Application deadline: 4 February 2016
    Application status: CLOSED

    Overview

    This course will present all the bioinformatics tools required to analyze RNA-seq gene expression data, from the raw data to the biological interpretation. This two-day course will discuss the following topics:
    • Quality control and reads cleanup
    • RNAseq reads mapping to genome & transcriptome
    • Gene reads counting, gene & exons differential expression
    • GO enrichment and pathway analysis

    Learning objectives

    At the end of the course attendees will:

    • Understand advantages and pitfalls for RNA sequencing
    • Be able to design their own experiment
    • Practise the downstream analysis using command line software (QC, mapping, counting, Diff Expression, gene enrichment, pathway analysis)

    Prerequisites

    Knowledge / competencies:

    • Participants should already have a basic knowledge in Next Generation Sequencing (NGS) techniques or already followed the Introduction to NGS course;
    • A basic knowledge of the R statistical software (http://www.r-project.org/) is also required.

    Location

    Nr. 215 / 2. OG West - Universität Bern, Hochschulstrasse 4

    Additional information

    Coordination: Diana Marek - SIB Training and Outreach

    You are welcome to register to the SIB courses mailing-list to be informed of all future courses and workshops, as well as all important deadlines using the form here.

    For more information, please contact training@isb-sib.ch.

  • Before the beginning of the course, you will need to have an emulation of a linux OS (virtual machine) on your computer to be able to access all the data and software you will use during the practicals.

    Technical: Participants should bring their own laptop (mininum 4GB RAM and 30 GB of free hard disk space) with R, Virtualbox software installed and the NGS_VM.ova virtual image deployed.

    To this end, you first need to have virtualbox installed on your computer. Please download and install version the latest version of virtualbox

    Then download the virtual image (.ova) here (Almost 9 GB file, it may take long to download) and import it into virtualbox (Around 30 min maximum). Then start the virtual image to check it works on your computer (password: user-SIB).

    If at the end of the procedure, you are still not able to run the virtual machine, please contact us sufficiently in advance at training@isb-sib.ch as no technical problem with the virtual machine will be handled during the course.


    Please also note that you need a computer with minimum of 4 GB memory. The virtual machine itself requires 3 GB memory. And at least 30 GB free space on your hard disk.

  • Monday 15 February

    9:15 - 10:30: Introduction to RNA-sequencing

    • Experimental design: challenges, considerations, strategies

    10:30 - 11:00: Coffee break

    11:00 - 12:30: Sequencing archives, SRA, ENA and DDBJ

    • File format - Quality Control - subsetting

    12:30 - 13:30: Lunch break

    13:30 - 15:00: Alignment to a reference genome/transcriptome

    • TopHat
    • STAR

    15:00 - 15:30: Coffee break

    15:30 - 17:00: RPKM/FPKM (Reads/Fragments Per Kilobase of transcript per Million mapped reads) Vs. Read counts

    • Practicals "htseq"

    Tuesday 16 February

    9:00 - 10:30: Preparing data for diff expression analysis

    • R- session

    10:30 - 11:00: Coffee break

    11:00: 12:30: Differential expression

    • Practicals using DESeq2 (R-statistics)

    12:30 - 13:30: Lunch break

    13:30 - 15:00: Gene Ontology and GO enrichment analysis

    • Practicals using Goseq (R-statistics)

    15:00 - 15:30: Coffee break

    15:30 - 17:00: Differentially enriched Pathways finding

    • Practicals using Pathview (R-statistics)

    17:00- 17:30: Optional exam