IGES Journal Club

IGES hosts regular virtual journal clubs throughout the year to increase IGES members' familiarity with emerging and classic literature in genetic epidemiology and to foster discussion and networking among members. Information about planned tasks will be published on this website, send to the IGES mailing list and posted on Facebook and Bluesky.

Do you have any suggestions for interesting topics, papers or presenters for further talks?

Or would you like to support us in organizing the Journal Club? Please contact Silke Szymczak ([email protected])

The organizing team of the IGES Journal Club:
Silke Szymczak, University of Lübeck, Germany
Cheryl Cropp, Morehouse School of Medicine, Atlanta, GA, USA
Heejong Sung, National Institute of Mental Health, NIH, Bethesda, MD, USA 

Stay tuned for the upcoming talks!

 


Previous presentations:

Presenter: Yu Shi
Paper title: Yield of genetic association signals from genomes, exomes and imputation in the UK Biobank

Presenter: Jasper Hof
Paper title: Fast and accurate recurrent event analysis for genome-wide association studies

Presenter: Zhiwen (Owen) Jiang
Paper title: The sequence kernel association test for multicategorical outcomes

Presenter: Dr. Anji Musick
Paper Title: The All of Us Research Program Data Resources and Access

Presenter: Mafalda Figueiredo Dias
Paper title: Disease variant prediction with deep generative models of evolutionary data

Presenter: Scott Ritchie
Paper title: Integrative analysis of the plasma proteome and polygenic risk of cardiometabolic diseases

Presenter: Sharon Lutz
Paper title: Caution against examining the role of reverse causality in Mendelian Randomization

Presenters: Farhad Hormozdiari and Cory McLean
Paper title: DeepNull models non-linear covariate effects to improve phenotypic prediction and association power

Presenter: Jenna Ballard
Paper title: Shared components of heritability across genetically correlated traits

Presenter: Ying Wang
Paper title: Global biobank analyses provide lessons for computing polygenic risk scores across diverse cohorts