Table 1.

Estimation of model parameters $\hat{\alpha }\mathit{and}\hat{\beta }$ under different α and β with fixed number of cells, prct, s, and gene number = 15,000. Comparing with the noise model in Eq. 9, we have obtained fairly low RMSE in each condition

Simulation parameters					Regression results
# of cells	Prct (%)	s	α	β	$\hat{\alpha }$	$\hat{\beta }$	RMSE	RMSE (Eq. 9)
1,000	10	2	0	1	0.0003 ± 0.0002	1.0293 ± 0.0014	0.0074 ± 0.0006	0.044 ± 0.010
				1.2	0.0004 ± 0.0003	1.2187 ± 0.0024	0.0047 ± 0.0006	0.066 ± 0.020
				1.5	0.0007 ± 0.0004	1.5032 ± 0.0039	0.0028 ± 0.0007	0.091 ± 0.019
			0.15	1	0.1557 ± 0.0005	1.0116 ± 0.0009	0.0047 ± 0.0003	0.049 ± 0.008
				1.2	0.1562 ± 0.0007	1.1965 ± 0.0020	0.0038 ± 0.0004	0.030 ± 0.004
				1.5	0.1569 ± 0.0007	1.4756 ± 0.0047	0.0043 ± 0.0006	0.017 ± 0.001
			0.5	1	0.5146 ± 0.0013	1.0020 ± 0.0010	0.0038 ± 0.0004	0.060 ± 0.006
				1.2	0.5161 ± 0.0011	1.1837 ± 0.0023	0.0039 ± 0.0003	0.047 ± 0.006
				1.5	0.5187 ± 0.0016	1.4561 ± 0.0045	0.0054 ± 0.0005	0.030 ± 0.004