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VERSION:2.0
PRODID:icalendar-ruby
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BEGIN:VEVENT
DTSTAMP:20260618T041116Z
UID:b2be5c03-cb2c-4acd-a6cc-23a4bb4cbf3d
DTSTART:20220406T090000Z
DTEND:20220406T170000Z
DESCRIPTION:Rare variants contribute to development of familial cancer.  G
 enes carrying rare variants may contribute to molecular mechanisms of spor
 adic cancers.  Historically\, many of the rare variants were discovered b
 y co-segregation with the disease in cancer families.  However\, recent p
 rogress in population scale sequencing opens new opportunities for using a
 ssociation analysis for detection of rare variants.  \n\nThe standard me
 thods 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) aggre
 gating of variants per gene (or pathway)\, (ii) weighting by biological si
 gnificance and allelic frequency\, and (iii) applying permutation-style te
 sts for estimating statistical significance.  \n\nThe webinar will discu
 ss these features of rare-variant analysis and illustrate their implementa
 tion using SKAT R library. \n\n 
LOCATION:\, 
SUMMARY:Methods for rare-variant association analysis
URL;VALUE=URI:https://www.ebi.ac.uk/training/events/methods-rare-variant-as
 sociation-analysis
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