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UID:20250506T201655EDT-9012nL4BeP@132.216.98.100
DTSTAMP:20250507T001655Z
DESCRIPTION:Abstract: The role of rare genetic variation in the etiology of
  complex disease and the optimal study design for identifying rare variant
 s remains unclear. However\, the development of next generation sequencing
  technologies offers the experimental opportunity to address these questio
 ns. Several novel statistical methodologies have been recently proposed to
  assess the contribution of rare variation to complex disease etiology. Ne
 vertheless\, no empirical estimates comparing their relative power are ava
 ilable\, and the magnitude of the contribution of very rare variants to th
 e statistical power of gene-based association tests is unknown. We therefo
 re assessed the parameters that influence their statistical power in 1\,99
 8 individuals Sanger-sequenced at seven genes by modeling different distri
 butions of effect\, proportions of causal variants\, and direction of the 
 associations (deleterious\, protective\, or both) in simulated continuous 
 trait and case/control. Our results demonstrate that the power of recently
  proposed statistical methods depend strongly on the underlying hypotheses
  concerning the relationship of phenotypes with each of these three factor
 s. As vary rare variants constitute the majority of variants identified in
  sequencing studies\, these findings suggest that careful attention need t
 o be placed on the plausible relationship that exist between very rare var
 iants and common disease. Sensitivity analyses are therefore recommended t
 o compare the stability of the results arising from different methods\, an
 d promising results should be replicated using the same method in an indep
 endent sample. These findings provide guidance in the analysis and interpr
 etation of the role of rare base-pair variation in the etiology of complex
  traits and diseases.
DTSTART:20120911T193000Z
DTEND:20120911T203000Z
LOCATION:1020 Pine Ave West\, Room 25\, Purvis Hall\, CA\, QC\, Montreal\, 
 H3A 1A2\, 1020 avenue des Pins Ouest
SUMMARY:Martin Ladouceur - 'Challenges with rare variant methodologies via 
 sequencing studies'
URL:/epi-biostat-occh/channels/event/martin-ladouceur-
 challenges-rare-variant-methodologies-sequencing-studies-35
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