High throughput sequencing in disease studies, Short Course

  • N/A
    Application Deadline
  • 4 days
  • Tuition
  • English (take IELTS)
  • Overview
  • Programme outline
  • Key facts
  • Admission requirements
  • Fees and funding


A short course taught in London by the Bloomsbury Centre for Genetic Epidemiology and Statistics, a joint centre of LSHTM and UCL. Applicants for this course may also be interested in our companion course: Introduction to Genetic Epidemiology in the GWAS era


Rapidly developing technologies now allow genomes to be sequenced more quickly and cheaply than ever before. This course will cover state of the art methods and applications of next generation sequencing. The course runs over 4 days and participants will be introduced to tools for analysing high throughput sequence data, including methods for measuring copy number variants and allele-specific expression, and conducting disease association analysis with sequence data. There will be considerable opportunities to gain practical experience with new data types such as whole genome sequence, RNA- and ChIP-seq data. By the end of the course participants will have a broad knowledge of the state of the art and will be well equipped to analyse their own data. This course follows the companion course Introduction to Genetic Epidemiology in the GWAS era.

Detailed Programme Facts

Programme Structure

The course consists of alternating lectures and computer practical sessions. Computer practicals will use free software which will be provided. Comprehensive course notes will be provided at the start of the course.

Course Content

Analysis of High-Throughput Sequencing data

  • Introduction to Linux, R and bioinformatics
  • Sequencing technologies
  • Data formats, quality control and alignment
  • Assembly and annotation of genomes
  • SNP, indel and structural variant calling
  • 1000 Genomes data and accessing data from the short read archive
  • RNA-seq and ChIP-seq analysis
  • Applications of sequence data (phylogenetics assessing population structure, association studies and detection of genic selection)

Methods of Assessment

There is no formal assessment but a certificate of attendance will be provided.


Vincent Plagnol and Taane Clark

Academic Requirements

Participants should have a working knowledge of genetics, epidemiology or bioinformatics, and have an interest in acquiring up to date knowledge about high throughput sequencing. A basic knowledge of statistics is required and previous experience with statistical computing packages such as R would be an advantage. A basic introduction to R is provided at the beginning of this course, and a self-guided introduction to R can follow the documentation provided at http://cran.r-project.org/

Tuition Fee


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