Methods for rare-variant association analysis

Rare variants contribute to development of familial cancer. Genes carrying rare variants may contribute to molecular mechanisms of sporadic cancers. Historically, many of the rare variants were discovered by co-segregation with the disease in cancer families. However, recent progress in population scale sequencing opens new opportunities for using association analysis for detection of rare variants.

The standard methods of association analysis were developed for common variants. While the standard regression framework and population stratification approaches hold in the rare-variant analysis, it may additionally require (i) aggregating of variants per gene (or pathway), (ii) weighting by biological significance and allelic frequency, and (iii) applying permutation-style tests for estimating statistical significance.

The webinar will discuss these features of rare-variant analysis and illustrate their implementation using SKAT R library.

Who is this course for?

This webinar is suitable forany researcher in life scienceswith an interest in genomics studies. No prior knowledge of bioinformatics is required, but an undergraduate level knowledge of biology would be useful.

Outcomes

By the end of the webinar you will be able to:

• Explore places of rare and common variants in genetic predisposition to cancer
• Identity challenges and statistical approaches to rare variant analysis
• Find how to implement rare variant analysis in SKAT R library

Speakers

• Alexey Larionov
  Cranfield University