Assessment of alternative genotyping strategies to maximize imputation accuracy at minimal cost

Table 2 Accuracy of imputation for twelve genotyping scenarios

Scenario	¹Genotyping strategy						²Imputation accuracy: R-squared
	Other	Grandparents		Parents		Testing individuals
		MGS + PGS	MGD + PGD	Sire	Dam
	n = 2436	n = 63	n = 86	n = 41	n = 73	n = 98	L6k	L3k	L384
s1	H	H	H	H	H	L	.996	.990	.967
s2	H	H	H	H	L	L	.991	.990	.952
s3	H	H	H	L	L	L	.989	.984	.941
s4	H	H	L	H	L	L	.991	.985	.935
s5	H	H	0	H	0	L	.981	.968	.888
s6	H	H	H	0	0	L	.984	.974	.910
s7	0	0	0	H	H	L	.958	.937	.870
s8	0	0	0	H	L	L	.841	.808	.728
s9	0	0	0	H	0	L	.850	.794	.719
s10	0	H	H	H	0	L	.988	.977	.910
s11	H	L	L	L	L	L	.975	.964	.888
s12	H	0	0	0	0	L	.953	.931	.817

¹Animals were split into groups (ordered by generation) of testing individuals, their parents, and their grandparents; grandparents were further divided into two groups: MGS + PGS which included maternal grandsire and paternal grandsire, and MGD + PGD which included maternal granddam and paternal granddam; the remaining individuals were placed in the “Other” category; groups of animals were either genotyped at high-density (H), low-density (L) or not genotyped (0); ²Imputation accuracy (R-squared) for scenarios using SNP panels L6k, L3k and L384 on animals genotyped at low density.

ISSN: 1297-9686