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SUMMARY:Advances in Linear Mixed Models for Genome-Wide Association Studie
 s
DTSTART:20130827T121500
DTEND:20130827T131500
DTSTAMP:20260510T202435Z
UID:010af7a06a874c406e151b24750fdbd33e6fe11bca02fb8bff58a653
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Christoph Lippert\, Senior Researcher\, eScience Group\, M
 icrosoft Research\, Los Angeles.\nIn my talk I am going to give an introdu
 ctory overview over our work on FaST-LMM\, an accurate and efficient metho
 d to correct for confounding by population structure and family relatednes
 s in genome-wide association studies. I am going to highlight two flaws in
  standard GWAS analyses using the linear mixed model that lead to a loss i
 n power and show simple and elegant ways to avoid them. The resulting meth
 od achieves better correction\, increased power to detect true association
 s and is extremely scalable. Finally\, I will talk about a recent extensio
 n of FaST-LMM to association tests of sets of multiple genetic markers\, f
 or example all variants contained in a gene or in a pathway.\nThe FaST-LMM
  software is available at:http://research.microsoft.com/en-us/um/redmond/p
 rojects/MSCompBio/Fastlmm/
LOCATION:SV.1717A http://plan.epfl.ch/?lang=fr&room=SV.1717A
STATUS:CONFIRMED
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