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Introduction to RNA-seq and ChIP-seq data analysis

Description

The aim of this course is to familiarize the participants with the primary analysis of datasets generated through two popular high-throughput sequencing (HTS) assays: ChIP-seq and RNA-seq.

This course starts with a brief introduction to the transition from capillary to high-throughput sequencing (HTS) and discusses quality control issues, which are common among all HTS datasets. Next, we will present the alignment step and how it differs between the two analysis workflows. Finally, we focus on dataset specific downstream analysis, including peak calling and motif analysis for ChIP-seq and quantification of expression, transcriptome assembly and differential expression analysis for RNA-seq.

 

Trainers

Guillermo Parada, Sanger Institute

Konrad Rudolph, University of Cambridge

Luigi Grassi, University of Cambridge

Myrto Kostadima, EMBL-EBI

Sandra Cortijo, The Sainsbury Laboratory

 

Audience and Prerequisites

  • Basic experience of command line UNIX
  • Sufficient UNIX experience might be obtained from one of the many UNIX tutorials available online.
  • Basic knowledge of the R syntax
  • For a real beginner's introduction into R see here. More advanced R instructions can be found at Quick-R or An Introduction to R
  • Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals

 

Syllabus, Tools and Resources

During this course you will learn about:

  • High-throughput sequencing technology
  • Quality control of raw reads: FASTQC and fastx toolkit
  • Considerations on experiment design for ChIP-seq and RNA-seq
  • Read alignment to a reference genome: Bowtie and Tophat
  • File format conversion and processing: UCSC tools and samtools
  • Peak calling: MACS
  • Motif analysis: MEME
  • Quantification of expression and guided transcriptome assembly: Cufflinks
  • Differential expression analysis: Cuffdiff

 

Learning Objectives

After this course you should be able to: 

  • Understand the advantages and limitations of the high-throughput assays presented
  • Assess the quality of your datasets
  • Understand the difference between splice-aware and splice-unaware aligners
  • Perform alignment and peak calling of ChIP-seq datasets
  • Perform alignment, quantification of expression and guided transcriptome assembly of RNA-seq datasets

 

Links

Book Here

 

Timetable

Day 1
09:30 - 10:00  Lecture: Next generation sequencing overview 
10:00 - 10:15  Tea/coffee break 
10:15 - 12:30  Lecture/Practical: data retrieval practical 
12:30 - 13:30  Lunch 
13:30 - 14:30  Lecture & Practical: NGS quality control 
14:30 - 15:15  Lecture: Introduction to ChIP-seq 
15:15 - 15:30  Tea/coffee break 
15:30 - 17:30  Practical: ChIP-seq analysis 
Day 2
09:30 - 10:00  Lecture: Introduction to RNA-seq 
10:00 - 10:15  Tea/coffee break 
10:15 - 12:00  Practical: RNA-seq analysis - alignment 
12:00 - 13:00  Lunch 
13:00 - 15:00  Practical: RNA-seq - Transcriptome assembly 
15:00 - 15:15  Tea/coffee break 
15:15 - 17:30  Practical: RNA-seq analysis - Differential expression analysis 

 

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