Inclusion Bias Affects Genetic Analyses in Biobanks

Learn how inclusion bias impacts genetic analyses in biobanks through this 26-minute conference talk from the Computational Genomics Summer Institute. Explore the systematic biases that occur when certain populations are underrepresented or overrepresented in biobank datasets, and understand how these biases can skew genetic research findings and limit the generalizability of results across diverse populations. Examine the mechanisms behind inclusion bias, its effects on genome-wide association studies (GWAS), and the implications for precision medicine and healthcare equity. Discover strategies and methodological approaches to identify, quantify, and mitigate inclusion bias in large-scale genetic datasets to ensure more representative and robust genomic research outcomes.