BIF807 - Data Driven Approaches to Analysis

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Last revision date Feb 13, 2019 2:01:11 PM
Last review date Feb 13, 2019 2:01:11 PM

Subject Title
Data Driven Approaches to Analysis

Subject Description

The aim of this course is to provide the students with hands-on analysis experience required in the workforce. The students will begin with an introduction to next-generation sequencing data. They will learn how to align this data, run basic quality control metrics and perform standard data analysis including single nucleotide variant calling, copy number aberration analysis, the identification of structural variances and the analysis of RNA-seq data. They will use open source tools that are commonly used in the field. The students will learn how to visualize their data throughout the course and gain experience working on a high performance computer cluster.

Learning Outcomes
Upon successful completion of this subject the student will be able to:

  • Describe the standard data formats used in the field (SAM/BAM and VCF formats).
  • Describe the different types of mutations we can detect with DNA-seq data (ie SNVs, CNVs, SVs) and demonstrate the ability to use different tools to call these mutations in our data.
  • Describe the different databases readily used in the field (ie dbSNP, COSMIC etc) and how to annotate mutations with these databases.
  • Determine differentially expressed genes using RNA-seq.
  • Visualize data using tools like R, IGV etc.
  • Process a larger dataset as a team to explore the different ways to analyse data (ie recurrent mutations) and present results to the class.
  • Demonstrate an understanding of project management.
  • Explore and utilize project-management resources and tools.

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