Skip to main content

Table 3 Time (in s) and memory (in MiB) for execution of Scanpy, SC3 and Seurat methods in several single cell banks

From: A cell abundance analysis based on efficient PAM clustering for a better understanding of the dynamics of endometrial remodelling

   

Method

Data

Number of

Number of

Scanpy

SC3

Seurat

set

cells

genes

Time

Memory

Time

Memory

Time

Memory

Wang

71,032

100

81.97

9194.92

(1)

123.75

483.89

500

100.69

9541.20

(1)

151.63

1238.48

4000

229.94

11786.49

2907.28

8334.96

299.47

5828.26

all

178.63

11572.80

6202.98

40560.79

717.55

27332.94

Garcia

100,307

100

117.89

13616.54

(1)

202.43

476.88

500

142.09

14174.46

(1)

204.96

940.13

4000

338.65

17515.35

3047.56

8411.55

347.43

5397.71

all

340.17

12055.15

6050.07

51085.32

1198.42

32640.66

Fonseca

118,144

100

120.84

8014.76

(1)

191.96

448.31

500

159.91

8944.68

(1)

252.76

1002.43

4000

388.47

12011.64

2606.85

9017.33

415.30

4996.09

all

178.63

11572.80

4752.91

73529.04

1678.49

31231.88

Merge

289,483

100

638.00

30738.78

(1)

631.02

950.68

500

490.14

32033.64

(1)

706.44

2266.57

4000

1111.51

40586.07

2960.67

21616.60

1017.365

13205.54

all

1454.21

41961.79

(2)

(2)

  1. SC3 was applied with 64 threads; Scanpy and Seurat do not allow the number of threads to be chosen
  2. (1): Application of SC3 with 100 and 500 genes caused a program error
  3. (2): Program crashes without error messages due to memory exhaustion on a 256 GiB machine