RNA-seq: From quality control to pathway analysis

Date 21 - 22 January 2019
Speaker(s) Walid Gharib, Irene Keller
ECTS 0.5
Fees *academic: 120 CHF   -   for-profit: 600 CHF
Cancellation deadline 7 Jan 2019
City Bern
*academic fee includes non for-profit organisations as well as unemployed participants at the time of application.

Please note that this course is oversubscribed with a long waiting list.

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

Audience

This course is intended for life scientists or bioinformaticians with basic knowledge in Next Generation Sequencing and willing to acquire the necessary skills to analyse RNA-seq gene expression data.

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 Unix and the R statistical software is also required.

Technical: Participants should bring their laptop (mininum 4GB RAM and 30 GB of free hard disk space).

Location

University of Bern main building, Hochschulstrasse 4, room 304, 3. OG Ost.

Application

Please note that this course is oversubscribed with a long waiting list.

The registration fees are 120 CHF for academics and 600 CHF for for-profit companies. This includes course content material and coffee breaks.

Deadline for registration and free-of-charge cancellation is set to January 07. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to this and other general conditions, available here.

You will be informed by email of your registration confirmation. Upon reception of the confirmation email, participants will be asked to confirm attendance by paying the fees within 5 days.

Additional information

Organizer: Patricia Palagi, SIB Training Group

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@sib.swiss.

Schedule

Day1:
9:15 - 10:30:  - Introduction to RNA-sequencing
                       - Experimental design: challenges, considerations, strategies
                       - Examples
10:30 - 11:00: Coffee Break
11:00 - 12:30: - Sequencing archives, SRA, ENA and DDBJ
                        - Practicals using SRA-tools
                        - File format - Quality Control - subsetting
12:30 - 13:30: Lunch break
13:30 - 15:00: - Interpretation of a Fastqc report and acting upon for cutting/trimming reads
                        - Trimming/filtering quality control - Practicals
15:00 - 15:30: Coffee break
16:00 - 17:00: - Alignment to a reference genome/transcriptome
                        - TopHat
                        - STAR

Day2:
9:00 - 10:30: Expression quantification:
                       - FPKM (Fragments Per Kilobase Of Exon Per Million fragments mapped) vs. Counting mapped fragments
                       - Practicals using htseq-count
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)