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Table 2 Estimation of model parameters \( \hat{\alpha}\ and\ \hat{\beta} \) under different prct and s with fixed number of cells, α, β, and gene number = 15,000

From: Detection of high variability in gene expression from single-cell RNA-seq profiling

Simulation parameters Regression results
# of cells α β s Prct (%) \( \hat{\alpha} \) \( \hat{\beta} \) RMSE RMSE (Eq. 9)
1,000 0.15 1.2 1 10 0.1563 ± 0.0005 1.1965 ± 0.0018 0.0037 ± 0.0003 0.028 ± 0.002
30 0.1579 ± 0.0006 1.2017 ± 0.0019 0.0048 ± 0.0003 0.026 ± 0.001
50 0.1612 ± 0.0009 1.2076 ± 0.0023 0.0071 ± 0.0005 0.027 ± 0.001
2 10 0.1563 ± 0.0005 1.1961 ± 0.0019 0.0040 ± 0.0005 0.033 ± 0.007
30 0.1612 ± 0.0017 1.2015 ± 0.0024 0.0077 ± 0.0014 0.036 ± 0.001
50 0.1713 ± 0.0014 1.2080 ± 0.0024 0.0147 ± 0.0012 0.050 ± 0.002
3 10 0.1572 ± 0.0012 1.1963 ± 0.0026 0.0056 ± 0.0009 0.048 ± 0.008
30 0.1649 ± 0.0010 1.1997 ± 0.0027 0.0122 ± 0.0011 0.054 ± 0.002
50 0.1775 ± 0.0012 1.2078 ± 0.0030 0.0225 ± 0.0011 0.096 ± 0.003