Table 2 |
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|
Congruencies across different endpoints and different feature-selection methods |
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|
Same endpoint but different feature selection (FS) |
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|
Endpoint |
Gene-level |
Level of canonic-pathway maps |
|
|
||
|
ER status |
0.541 |
0.573 |
|
pCR |
0.544 |
0.572 |
|
pCR(ER-) |
0.593 |
0.532 |
|
|
||
|
Same FS but different endpoints |
||
|
FS |
Gene-level |
Level of canonic-pathway maps |
|
|
||
|
FS1 |
0.300 |
0.290 |
|
FS2 |
0.299 |
0.274 |
|
FS3 |
0.291 |
0.278 |
|
FS4 |
0.295 |
0.291 |
|
FS5 |
0.272 |
0.282 |
|
|
||
|
The table shows that kappa statistics (that is, congruency) are high for different feature-selection methods for the same endpoint but are low for the same feature-ranking method for different endpoints. Both gene-level and pathway-level analyses show similar results. |
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|
Popovici et al. Breast Cancer Research 2010 12:R5 doi:10.1186/bcr2468 |
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