,
yp
es were the OS and ORT models. The maximum Type I error rate
st 23% for the OS model for four outliers data, which resulted in
I errors.
e 6.7. Prediction errors of non-DEGs for the simulated data for all tests.
Outlier
1
2
3
4
5
T test
0
0
0
0
0
Limma
0
0
0
0
3
COPA
0
2
9
15
17
OS
78
78
88
91
84
ORT
46
42
51
54
61
MOST
8
16
21
17
17
LSOSS
0
0
0
0
0
DOG
0
0
0
0
0
e 6.8. A comparison of prediction error of DEGs for the simulated data.
Error of up-regulated DEGs
Error of down-regulated DEGs
1
2
3
4
5
1
2
3
4
5
0
2
7
8
10
6
10
10
10
10
0
0
6
8
10
4
10
10
10
10
2
1
1
1
2
50
50
50
48
40
0
0
0
0
0
43
42
37
37
37
4
3
3
3
2
38
34
37
36
38
39
37
36
33
37
49
48
48
50
47
31
36
36
39
37
50
50
50
50
50
0
0
0
0
4
2
2
3
3
2
6.8 shows the error statistics (Type II error) of all tests for the
gulated DEGs and the up-regulated DEGs. Except for the MOST
SOSS models, others had small errors for the up-regulated DEGs.
not a surprise for the COPA, OS and ORT models. These
ms were developed based on the similar working principle, i.e.,
the outliers were present in the case replicates only. The MOST
SS models showed unreasonable results because many DEGs
outliers were also mis-classified. In terms of the down-regulated
was not a surprise when the COPA, OS and ORT models returned
performance. As aforementioned, these three algorithms only