Speed Comparison of four programs:
DNAcopy: R package, version.1.10.0
CGHseg: Matlab program
CLAC: R package, version 1.1-2
cghFLasso: R package, version 1.0.0
1. Pre-specify chromosome length p=100, 500, 1000, 2000, 5000, 8000
2. Random sample 50 genome segments of length p from 17 Breast Cancer CGH arrays.
3. Apply each method on the 50 segments, and record the CPU time.
Mean and the standard deviation (in the parenthesis) of the CPU time (seconds):
|
|
P=100 |
P=500 |
P=1000 |
P=2000 |
P=5000 |
P=8000 |
|
DNAcopy |
0.151 (0.113) |
1.243 (0.804) |
3.669 (1.135) |
8.455 (2.854) |
14.023 (8.422) |
19.810 (16.881) |
|
CGHseg |
0.063 (0.008) |
0.445 (0.016) |
1.223 (0.041) |
4.205 (0.104) |
37.94 (0.621) |
98.36 (1.828) |
|
CLAC |
0.049 (0.003) |
0.086 (0.013) |
0.157 (0.037) |
0.368 (0.073) |
0.965 (0.296) |
Does not run. |
|
cghFLasso |
0.025 (0.013) |
0.140 (0.017) |
0.334 (0.036) |
0.840 (0.056) |
2.5814 (0.331) |
7.775 (0.182) |
For an aCGH data set with 200 samples, the rough run time (hour) is:
|
Length of Array |
DNAcopy |
CGHseg |
CLAC |
cghFLasso |
|
20K |
3.87 |
1.46 |
0.18 |
0.38 |
|
100K |
14.82 |
29.74 |
Does not run |
2.33 |