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BSU Seminar: "Genome-wide genetic models for association, heritability analyses and prediction"

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If you have a question about this talk, please contact Alison Quenault .

This will be a free hybrid seminar. To register to attend virtually, please click here: https://us02web.zoom.us/meeting/register/tZcpcuipqTMuGtP_pIJrVQDLQGbP3ndqAh-N

Although simultaneous analysis of genome-wide SNPs has been popular for over a decade, the problems posed by more SNPs than study participants (more parameters than data points), and correlations among the SNPs, have not been adequately overcome so that almost all published genome-wide analyses are suboptimal. While there has been much attention paid to the shape of prior distributions for SNP effect sizes, we argue that this attention is misplaced. We focus on what we call the “heritability model”: a low-dimensional model for the expected heritability at each SNP , which is key to both individual-data and summary-statistic analyses. The 1-df uniform heritability model has been implicitly adopted in a wide range of analyses. Replacing it with better heritability models, using predictors based on allele frequency, linkage disequilibrium and functional annotations, leads to substantial improvements in estimates of heritability and selection parameters over traits, and over genome regions, as well as improvements in gene-based association testing and prediction. Key collaborators Doug Speed, Aarhus, Denmark and Melbourne PhD student Anubhav Kaphle.

This talk is part of the MRC Biostatistics Unit Seminars series.

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BN3-05 (Sigproc Meeting Room), 3rd Floor of CUED UTC Cambridge, Robinson Way, Cambridge, CB2 0SZ Virtual Meeting; meet.google.com/edp-ekea-vcr

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