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- Gene Ontology and biological networks
- Methods for exploring newly-annotated species in Ensembl Rapid Release
- Discovering biological information from mass spectrometry-based proteomics
- Methods in bioimage analysis
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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 with Alexey Larionov (Lecturer, Cranfield University), recorded on 06 April 2022, discusses these features of rare-variant analysis and illustrates their implementation using SKAT R library.
By the end of the webinar recording 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