Site Education SciNet

Next generation sequencing is revolutionizing the way molecular sciences and biology is performed while providing a population-level understanding of genetic variation in organisms. In this course, you will be introduced to data types in next generation sequencing, analysis methods and best practices to go from raw sequencing data to fully reconstructed genomes. Attendees will also be exposed to variant calling methods to assess genetic variation and the use of parallel methods to scale large analysis on a high-performance computing cluster. Principles in this course can be applied to the other workshops in this stream for genome-wide association analysis and RNA sequencing analysis. -- Prerequisite: basic Linux command line skills

The class will cover basic pipeline of pre-alignment QC of FASATQ files, read alignments to the reference genome, Post alignment visualization using IGV, and differential expression analysis using R. If time permits, enrichment analysis using GSEA will also be covered.

This 3 hours course will focus of data cleaning and statistical analysis of large scale genetic data using PLINK and R softwares. We will use SciNet to run the PLINK analytical workflow to perform markers and individuals quality control, including population stratification and ancestry followed by association analysis between genetic variation and trait of interest. R-software (basic R plotting and ggplot package) will be use to visualize the results.

Part of the 2017 Ontario Summer School.