Background
Methods
Experimental data
Statistical methods
SAMGSR
Modification to SAMGSR for longitudinal data
Performance statistics
Statistical language and packages
Results
Injury application
Method | # of genes | Using 5-fold CVs | On the test set | ||||||
---|---|---|---|---|---|---|---|---|---|
Error | GBS | BCM | AUPR | Error | GBS | BCM | AUPR | ||
L-SAMGSR1 | 97 | 0.442 | 0.268 | 0.515 | 0.576 | 0.356 | 0.230 | 0.535 | 0.622 |
EDGE1 | 1083 | 0.442 | 0.281 | 0.511 | 0.526 | 0.407 | 0.234 | 0.514 | 0.594 |
SAMGSR separatelya | > 400 | 0.419 | 0.246 | 0.510 | 0.559 | 0.428 | 0.243 | 0.511 | 0.553 |
P-SVM separately | > 1000 | 0.488 | 0.281 | 0.477 | 0.454 | 0.441 | 0.244 | 0.511 | 0.560 |
LASSO separately | 147 | 0.465 | 0.261 | 0.497 | 0.498 | 0.407 | 0.237 | 0.509 | 0.580 |
Simulations
Time 1 | Time 2 | Time 3 | Time 4 | Time 5 | ||
---|---|---|---|---|---|---|
# of genes | 19.84 | 19.14 | 13.68 | 9.30 | 11.00 | |
Simulation 1 | F13A1 (%) | 72 | 100 | 100 | 92 | 68 |
(Ave. # 32.06) | GSTM1 (%) | 0 | 0 | 62 | 22 | 0 |
# of genes | 182.38 | 56.18 | 35.44 | 30.94 | 123.84 | |
Simulation 2 | COX4I2 (%) | 96 | 0 | 0 | 0 | 4 |
(Ave. # 291.98) | RP9 (%) | 10 | 4 | 4 | 6 | 96 |