From: Bayesian compositional regression with microbiome features via variational inference
Method | \(\rho\) | TPR | FPR | L2 | PE |
---|---|---|---|---|---|
Lasso | 0 | 1 ± 0.000 | 0.365 ± 0.179 | 5.265 ± 0.699 | 0.432 ± 0.308 |
Lin | 0 | 1 ± 0.000 | 0.388 ± 0.164 | 5.310 ± 0.686 | 0.434 ± 0.331 |
Bates | 0 | 1 ± 0 | 0.029 ± 0.058 | 5.685 ± 0.580 | 0.358 ± 0.257 |
Selbal | 0 | 0.770 ± 0.091 | 0.000 ± 0.000 | 9.644 ± 0.762 | 1.810 ± 0.729 |
VB | 0 | 1 ± 0 | 0.008 ± 0.015 | 5.633 ± 0.492 | 0.378 ± 0.247 |
Lasso | 0.2 | 1 ± 0 | 0.334 ± 0.166 | 5.389 ± 0.623 | 0.471 ± 0.289 |
Lin | 0.2 | 1 ± 0 | 0.308 ± 0.164 | 5.321 ± 0.686 | 0.482 ± 0.295 |
Bates | 0.2 | 1 ± 0 | 0.022 ± 0.036 | 5.805 ± 0.454 | 0.445 ± 0.275 |
Selbal | 0.2 | 0.667 ± 0 | 0 ± 0 | 10.274 ± 0.549 | 1.364 ± 0.568 |
VB | 0.2 | 1 ± 0 | 0.003 ± 0.008 | 5.705 ± 0.438 | 0.416 ± 0.263 |
Lasso | 0.4 | 1 ± 0 | 0.378 ±0.141 | 5.384 ± 0.5875 | 0.523 ± 0.346 |
Lin | 0.4 | 1 ± 0 | 0.423 ± 0.141 | 5.358 ± 0.598 | 0.536 ± 0.333 |
Bates | 0.4 | 1 ± 0 | 0.019 ± 0.035 | 5.792 ± 0.427 | 0.417 ± 0.257 |
Selbal | 0.4 | 0.667 ± 0.024 | 0 ± 0 | 9.365 ± 0.547 | 0.945 ± 0.581 |
VB | 0.4 | 1 ± 0 | 0.008 ± 0.015 | 5.633 ± 0.492 | 0.441 ± 0.273 |