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SUMMARY:Analysis of Genetics linked EHR data: Understanding Selection Bias
  and Phenotyping Error - Professor Bhramar Mukherjee (University of Michig
 an)
DTSTART:20221209T110000Z
DTEND:20221209T123000Z
UID:TALK193594@talks.cam.ac.uk
CONTACT:Spencer Keene
DESCRIPTION:"In this talk I will share a decade of experience and exciteme
 nt of being involved with the Michigan Genomics Initiative\, a longitudina
 l biorepository at the University of Michigan Health System\, containing a
 dministrative healthcare data linked with genetic markers and many other e
 xternal data sources on nearly 100\,000 participants. This is a rich datas
 et with large p and large n. However\, a perioperative recruitment strateg
 y induces selection bias in the analytic sample. In addition\, we have an 
 incomplete capture of disease history leading to phenotype misclassificati
 on. I will present strategies to understand and reduce bias when these two
  sources are at play. Examples from COVID-19 and Cancer will be used to il
 lustrate that foundational principles of study design and sampling are cri
 tical to turn big data into reliable knowledge."\n
LOCATION:Heart and Lung Research Institute (ground floor)
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