Causal effect estimation in sequencing studies: a Bayesian method to account for confounder adjustment uncertainty

Table 1 Estimation results. Estimation of the ACE on SBP for two MAP4 SNVs at position 47956424 and position 47908815, chromosome 3

SNV	Data set	Method	BIAS	SEE	SSE	RMSE
47956424 (MAF = 0.3435)	Simulated phenotype	“True model”	0.166	1.206	1.121	1.131
		“Full model”	0.663	4.215	4.280	4.320
		BAC	0.440	1.587	1.277	1.347
	Q1	“True model”	0.006	0.996	1.105	1.102
		“Full model”	0.025	3.483	3.591	3.582
		BAC	0.089	1.313	1.203	1.203
47908815 (MAF = 0.0026)	Simulated phenotype	“True model”	1.617	3.771	3.844	4.161
		“Full model”	5.115	6.89	6.739	8.447
		BAC	3.438	5.322	5.329	6.331
	Q1	“True model”	0.129	3.115	3.113	3.108
		“Full model”	0.369	5.694	5.621	5.619
		BAC	0.179	4.419	3.964	3.958

BIAS is the difference between the mean of estimates of ACE and the true value; RMSE is the root mean square error; SEE is the mean of standard error estimates; SSE is the standard error of the estimates of ACE
Results are based on 200 simulated phenotypic or Q1 data sets. In simulated phenotypic data, the true ACE of SNV at position 47956424 (47908815) is −6.094 (−7.732). In Q1 data, the true ACE of the two SNVs is zero

ISSN: 1753-6561