An Introduction to the Analysis of the Next-generation Sequencing Data [EL019]

Detailed information about this course:

Description

This course provides an introduction to working with Next-Generation Sequencing (NGS) data. It targets individuals who have access to NGS data and want to learn how to work with this data and what the possibilities and limitations of NGS are. Lectures will be complemented with practical sessions in which the student will gain hands-on experience with various tools and techniques.Subjects that will be covered include:

• NGS: an introduction to methodology and techniques;
• Basic statistics of NGS data, e.g. coverage;
• Aligning the sequence reads;
• Calling sequence and structural variants;
• Dealing with various file formats (samtools, VCFtools, GATK);
• Annotating sequence and structural variants;
• Evaluating functional effects of the genetic variants on proteins;
• Conversion to other formats;
• Single variant and Collapsed genotype analyses with various tools (e.g. seqMeta, RAREMETAL and RVtest);
• Finding variants with recessive effects and compound heterozygosity;
• Search for rare variants in families and population based studies for complex phenotypes;
• Search for rare variants in Mendelian disorders, and
• Imputation of sequence variants.

See 'how to apply' for the course registration period.

Objectives

• Understand the main principles of genome sequencing technologies, data preparation, control and data analysis.
• Acquire tools and skills in Linux to analyze NGS data through the command line using dedicated tools and software for NGS data processing, variant calling, and quality control.
• Learn the principles of NGS data analysis in family-based studies and clinical case collections of monogenic and oligogenic disorders.
• Grasp the potential and drawbacks of applying genome sequencing technologies in population-based studies of complex traits.
• Understand the main principles of NGS data generation and analysis across other "–omics" layers, transcriptome, epigenome, microbiome.

Participant profile

Clinical researchers, clinical epidemiologists, molecular biologists, bioinformaticians and biostatisticians aspiring to run sequencing-based data analyses by themselves, or work with next-generation sequencing data and want to know how this is typically created. Some affinity with scripts and/or genetics is suggested.

Assessment

Assignment(s), Attendance