Sex-stratified linear mixed models: Non-binary traits (Item 3/3)

Sex-stratified GWAS can help shed light on sexual differences in genetic architecture. In Bernabeu et al (2021) we fit sex-stratified linear mixed models (using DISSECT) across a total of 530 phenotypes to assess the effects of sex on genetic effect estimates, and compared estimates between males and females in a search for genetic variants that presented significant differences in association to the traits considered. Here, the summary statistics of said efforts, pertaining to non-binary traits, are included. Each file contains the results for a single non-binary trait, as stated in the file name, using its corresponding UK Biobank trait code. Trait descriptions, including their respective UK Biobank codes, are stated in the “trait_description.tsv” file. For each trait (each .gz file), GWAS summary statistics obtained for over 9 million genetic variants across the genome (both autosomal, and X chromosome) and circa 450K individuals, as well as the results of the t-test comparing genetic effect estimates between the sexes, are included.