Fig. 2

Bar plots showing the proportion of variance explained using family-based methods and using molecular genetic data in related and unrelated samples. All of these analyses were performed using the same GS:SFHS data (n = 20,522, Education n = 22,406). Using related individuals and GREML-KIN, a sample size of 19,036 was available for general intelligence, and 18,528 for education after quality control. GREML-MS was conducted on unrelated individuals using a sample of n = 7019 for general intelligence and 6860 for Education. Estimates depicted in red were derived in the current study using GREML-KIN and show two sources of genetic variance. Bright red being common genetic effects captured by the GRM_g matrix and dark red being the additional genetic effects captured by exploiting the higher level of linkage disequilibrium between family members using the GRM_kin matrix. Estimates shown in shades of blue were derived using GREML-MS and indicate the variance explained using unrelated individuals with genotyped data imputed to the HRC reference panel. The estimates in dark green are taken from Marioni et al. [63] and show the total genetic effects using ASReml-R mixed model when relatedness is inferred using identity by descent