Training courses 2017: Training Course on Best practices for RNA-Seq data analysis

IMPORTANT DATES for this Training course:

Deadline for applications: 11 Sep 2017
Course date: 27-29 Sep 2017

VENUE: Campus di Fisciano, University of Salerno, Via Giovanni Paolo II n. 132, 84084 Fisciano (SA), Italy.

FEE: The fee will cover attendance to lectures and practicals, coffee breaks and lunches. The participants are expected to pay their own travel and accommodation costs:

candidates from a bioinformatics lab from one of the ELIXIR-IIB member institutions (see the list at the bottom): 120 euros
other candidates: 160 euros

A maximum of 25 candidates will be accepted. Selection will start on July 20th and those with an adequate profile will be accepted immediately.

Instructors

Fabrizio Ferré - Dept. of Pharmacy and Biotechnology, University of Bologna, Italy.
Loredana Le Pera - Center for Life Nano Science@Sapienza, IIT, Roma, Italy.
Giorgio Giurato - Lab. of Molecular Medicine and Genomics and Genomix4Life srl, University of Salerno.
Allegra Via - ELIXIR-IIB Training Coordinator, IBPM-CNR, Italy.

Organisers

Anna Marabotti (ELIXIR-IIB Training Team and University of Salerno, Italy)
Roberto Tagliaferri (University of Salerno, Italy)
Alessandro Weisz (Lab. of Molecular Medicine and Genomics, Department of Medicine, University of Salerno, Italy)
Loredana Le Pera (ELIXIR-IIB Training Team and CLNS@Sapienza, IIT, Italy)
Allegra Via (ELIXIR-IIB Training Coordinator, IBPM-CNR, Italy)

Course Description

Next-generation sequencing (NGS) of RNA libraries (RNA-Seq) has become increasingly common and it largely replaced microarray technology for gene expression profiling. The aim of this course is to get a deeper understanding of RNA-Seq experiments, providing a theoretical introduction to the data processing steps, together with practical sessions illustrating the use of the most popular data analysis tools. The classroom size is limited to 25 participants to optimize the learning and the interaction with the instructors. Starting from the raw sequenced data coming from different phenotypical samples (e.g disease vs healthy control samples), genes which are differentially expressed between the two conditions are determine. Some strategies are illustrated for detecting alternative splicing products, predicting novel isoforms and gene fusion events. Some methods for downstream analysis are described to give insight into how biological knowledge can be generated from RNA-Seq experiments. A lecture on single-cell RNA-Seq will provide an idea of how transcriptome data from individual cells is now emerging as a powerful tool, allowing the study of cell-to-cell gene expression heterogeneity in the same tissue.

Course objectives

Students will gain an understanding of:

experimental design
quality control
theoretical principles of RNA-Seq data analysis process
how to identify differentially regulated genes
how to identify alternative splicing events
how to identify gene fusion events
multiple testing correction
biological interpretation of RNA-seq data

Target audience

This course is aimed at PhD students and young researchers in the life science and computational biology field who are planning to use RNA-seq data and are looking for the best practices to analyze these types of data. Basic knowledge of UNIX/Linux operative system and the BASH command line is desirable; however, on the first day of the course, a practical tutorial will provide an introduction about shell usage and common commands. To apply for the course please fill in the application form, which includes a questionnaire; participants will be selected according to their profile and to their answers to the questionnaire.

Learning outcomes

After this course participants should be able to:

understand the importance of RNA-Seq experimental design
assess the quality of data
preprocess data
align data to a reference genome/transcriptome
perform a complete analysis of RNA-Seq data (Tuxedo Suite)
estimate known gene and transcript expression
discover alternative splicing events and novel isoforms
discover fusion gene events
perform differential expression analysis
perform functional enrichment analysis
summarize and interpret the RNA-seq analysis results

Course prerequisites

A basic understanding of molecular biology and transcriptomics is assumed. A basic knowledge of Linux (shell usage, common commands) and familiarity with elementary statistics are beneficial, but not essential.

Application Form

Programme

Course materials available from the github repository:
https://github.com/ELIXIR-IIB-training/RNASeq2017

Wednesday - 27 Sep 2017
09:15 - 10:00	Welcome and Opening. Participants' self-presentation
10:00 - 11:00	Lecture	An introduction to NGS and RNA-Seq
11:00 - 11:30	Coffee break
11:30 - 13:00	Lecture	Intro to the Linux command line
13:00 - 14:00	Lunch break
14:00 - 14:45	Lecture	Overview of the RNA-Seq data analysis process: from raw data (reads) to the differentially expressed gene list
14:45 - 15:30	Lecture	Preprocessing of RNA-Seq raw data: quality control, trimming, filtering
15:30 - 16:00	Coffee break
16:00 - 18:30	Practical	Linux tutorial - Raw data preprocessing
Thursday - 28 Sep 2017
09:15 - 09:30	Wrap up
09:30 - 10:30	Lecture	Alignment of RNA-Seq data
10:30 - 11:00	Coffee break
11:00 - 13:00	Practical	Alignment of RNA-Seq data
13:00 - 14:00	Lunch break
14:00 - 14:45	Lecture	Transcriptome Assembly and Quantifying Transcripts (Tuxedo Suite)
14:45 - 15:30	Lecture	Alternative splicing events – Fusion genes
15:30 - 16:00	Coffe break
16:00 - 17:45	Practical	Transcriptome Assembly – Quantifying Transcripts – Alternative splicing events
17:45 - 18:30	Talk	“About Single-cell RNA-Seq”
Friday - 29 Sep 2017
09:15 - 09:30	Wrap up
09:30 - 10:30	Lecture	Differential Expression Analysis (Tuxedo Suite)
10:30 - 11:00	Coffee break
11:00 - 13:00	Practical	Differential Expression Analysis - Fusion genes
13:00 - 14:00	Lunch break
14:00 - 15:00	Lecture	Downstream analysis: enrichment function analysis and beyond
15:00 - 16:00	Practical	Downstream analysis
16:00 - 16:30	Final wrap-up and feedback