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DTSTART:20241103T020000
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DESCRIPTION:SPEAKER : Yan Yu\, PhD\, Joseph S. Stern Professor of Business
  Analytics\, Department of Operations\, Business Analytics\, and Informat
 ion Systems\, University of Cincinnati TITLE : “Knowledge Integration Qua
 ntile Regression (KIQR) in Ultra-High Dimensions” ABSTRACT: We propose a 
 Knowledge Integration Quantile Regression (KIQR) framework for simultaneo
 us variable selection and estimation in ultra-high dimensions\, motivated
  by an application to identifying genetic risk factors for obesity from h
 undreds of thousands of single nucleotide polymorphisms (SNPs) in a cohor
 t study with a limited number of participants. KIQR integrates prior info
 rmation from external large-scale studies such as the GIANT consortium an
 d UK Biobank into a penalized quantile regression framework via a novel k
 nowledge integration mechanism that adaptively balances prior knowledge a
 gainst observed data while remaining robust to potential prior misspecifi
 cation. Focusing on high conditional quantiles of body mass index (BMI) m
 ost relevant to obesity risk\, KIQR addresses key limitations of standard
  genome-wide association studies (GWAS): the stringent significance thres
 hold\, the univariate marginal mean association\, and the lack of utiliza
 tion of prior knowledge. We establish oracle properties and large sample 
 properties of the penalized estimator under the non-differentiable check 
 loss via Huber approximation\, combined with a nonconvex SCAD penalty han
 dled through local linear approximation. Simulation studies further demon
 strate its effectiveness. Applied to the Framingham Heart Study\, KIQR id
 entifies three novel SNP associations: rs3798696 in TFAP2A\, rs7070523 in
  ITIH5\, and rs178260 in AIFM3\, which have not previously been reported 
 in the GWAS literature. YSPH values inclusion and access for all particip
 ants. If you have questions about accessibility or would like to request 
 an accommodation\, please contact Charmila Fernandes at Charmila.fernande
 s@yale.edu . We will try to provide accommodations requested by September
  29\, 2026.\n\nSpeaker:\nYan Yu\, PhD\n\nAdmission:\nFree\n\nFood:\nRefre
 shments at 3:45 PM\n\nDetails URL:\nhttps://medicine.yale.edu/event/ysph-
 biostatistics-seminar-tba-10-05-26/\n
DTEND;TZID=America/New_York:20261005T170000
DTSTAMP:20260928T235005Z
DTSTART;TZID=America/New_York:20261005T160000
GEO:41.303666;-72.932218
LOCATION:Yale School of Public Health (LEPH)\, 115\, 60 College Street\, N
 ew Haven\, CT\, United States
SEQUENCE:0
STATUS:Confirmed
SUMMARY:YSPH Biostatistics Seminar: “Knowledge Integration Quantile Regres
 sion (KIQR)   in Ultra-High Dimensions"
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