Analysis of High-Throughput Sequencing Data

Analysis of High-Throughput Sequencing Data is organized by EMBO - excellence in life sciences, University of Cambridge School of Clinical Medicine and would be held during Sep 05 - 10, 2016 at University of Cambridge, Cambridge, England, United Kingdom.

Audience :
This course is aimed at advanced PhD students and post-doctoral researchers who are applying or planning to apply high throughput sequencing technologies and bioinformatics methods in their research. Familiarity with the technology and biological use cases of high throughput sequencing is required, as is some experience with R/Bioconductor. 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
Peak calling: MACS, USeq and SISSR
Motif analysis: MEME
Quantification of expression and differential expression analysis and differential exon usage: R, DESeq, DEXSeq
Small non-coding RNA analysis: R, Reaper
Course overview :
The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of sequencing data under the guidance of the lecturers and teaching assistants.