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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