NGS Workshop 2015 Oxford

  • Instructors

    Dr David Langenberger
    CEO, ecSeq Bioinformatics
    Leipzig, Germany

    Dr Mario Fasold
    CTO, ecSeq Bioinformatics
    Leipzig, Germany

A Practical Introduction to NGS Data Analysis (in progress)

Total number of Available Spaces:  Nil 

Venue: ISIS Room, Oxford University IT Services, 7-19 Banbury Road, Oxford OX2 6NN, UK
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We are delighted to announce this Next Generation Sequencing training course/workshop, which will be conducted by ecSeq Bioinformatics.

The purpose of this workshop is to get a deeper understanding in High-Throughput Sequencing (HTS) with a special focus on bioinformatics issues. Advantages and disadvantages of current sequencing technologies and their implications on data analysis will be discovered. The participants will be trained on understanding their own HTS data, finding potential problems/errors therein and finally performing their own analyses using open source tools. In the course we will use a RNA-seq dataset from the current market leader, Illumina.

Each participant will have a dedicated workstation for the training.

Workshop Programme: 
Day 1: 13 April, Monday: 9.00-17.00 (including two refreshment breaks and a lunch break)
  1. Introduction to sequencing technologies from a data analysts viewSequence file formats (fastq)
    1. Mechanisms of instruments: Illumina, 454, IonTorrent and PacBio
    2. Sequencing protocols (mRNA-seq, microRNAseq, …)
    3. Capabilities & limitations: Error sources, biases & beyond
  2. Sequence file formats (fastq)
  3. Preparation of raw reads: quality control, adapter clipping
  4. Read mapping
    1. Alignment methods
    2. Mapping tools, mapping to a reference genome


Day 2: 14 April, Tuesday: 9.00-17.00 (including two refreshment breaks and a lunch break)
  1. Mapping output
    1. File formats (SAM/BAM)
    2. Samtools
    3. Bedtools
  2. Visualization of mapped readsGene expression quantification
    1. UCSC: Data format for upload
    2. IGV
  3. Gene expression quantification
  4. Differential expression analysis