Biobanks often contain several phenotypes relevant to diseases such as major depressive
disorder (MDD), with partly distinct genetic architectures. Researchers face complex
tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small
sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often
unclear. Here we propose to integrate these phenotypes to combine the benefits of each.
We use phenotype imputation to integrate information across hundreds of MDD-relevant …

Biobanks often contain several phenotypes relevant to a given disorder, and researchers
face complex tradeoffs between shallow phenotypes (high sample size, low specificity and
sensitivity) and deep phenotypes (low sample size, high specificity and sensitivity). Here, we
study an extreme case: Major Depressive Disorder (MDD) in UK Biobank. Previous studies
found that shallow and deep MDD phenotypes have qualitatively distinct genetic
architectures, but it remains unclear which are optimal for scientific study or clinical …