Random_Intensity_60_5a: 60 Cases, 60 Controls, 300 Peaks

Brian T. Luke (lukeb@ncifcrf.gov)
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BMDK Analysis

27 peaks selected as putative biomarkers by the 10 methods within BMDK

Peak catboot student dtgini dtinfg nnfeat chisq kruswal kolsmir extreme vartest
6     3 2            
18               4    
29 5         2        
33 3                  
51               4    
52           5        
90 4             4    
94         5   5      
103                 3  
105 1                  
114                 3  
116     4 5            
118   4     4   4     4
128   5               5
140   3 4   1   3 3   3
157                 2  
158       4         1  
159   1 1 3 3 4 1 1   1
162                 3  
177           5        
184 2                  
193   2     2   2 2   2
231     2 1            
239               4 3  
241           1     3  
260           2        
269                 3  

Peaks used in each of the best distance-dependent 6-nearest neighbor classifiers

Peak 1-ad 2-ad 3-ad 1-rd 2-rd 3-rd 2-cr 3-cr 2-sd 3-sd
6     X   X          
18                    
29                    
33           X   X   X
51                    
52                    
90                    
94           X   X   X
103                    
105                    
114                    
116     X       X   X  
118                    
128                    
140   X       X   X   X
157                    
158                    
159                    
162 X     X     X   X  
177         X          
184                    
193                    
231     X              
239                    
241   X                
260                    
269                    

Sensitivity, specificity, %undetermined, and quality (sensitivity + specificity - %undetermined) for each of the best distance-dependent 6-nearest neighbor classifiers using any of the 27 putative biomarkers.

Metric 1-ad 2-ad 3-ad 1-rd 2-rd 3-rd 2-cr 3-cr 2-sd 3-sd
Sens 78.3 71.2 73.7 77.6 71.4 67.6 70.2 73.1 70.2 74.0
Spec 73.3 66.7 65.0 71.2 68.5 78.0 72.2 74.5 71.7 72.5
%Undet 0.0 0.8 2.5 2.5 14.2 30.0 7.5 14.2 8.3 15.8
Quality 151.7 137.0 136.2 146.3 125.8 115.6 134.9 133.4 133.5 130.7

Sensitivity, specificity, %undetermined, and quality (sensitivity + specificity - %undetermined) for each of the best distance-dependent 6-nearest neighbor classifiers using any of the 27 putative biomarkers with the caveat that %Undetermined cannot exceed 5.0%.

Metric 1-ad 2-ad 3-ad 1-rd 2-rd 3-rd 2-cr 3-cr 2-sd 3-sd
Sens 78.3 71.2 73.7 77.6 None None 62.7 None 56.1 None
Spec 73.3 66.7 65.0 71.2 None None 61.4 None 73.7 None
%Undet 0.0 0.8 2.5 2.5 None None 3.3 None 5.0 None
Quality 151.7 137.0 136.2 146.3 None None 120.8 None 124.8 None

Fingerprint Analysis

Sensitivity, specificity and quality (sensitivity + specificity) for the best and 200th best decision tree constructed from any of the 300 peak intensities.  The evolutionary programming search used a population size of 200 and ran for 400 generations.  A decision node became a terminal node when it contained 1% (no samples) or 4% (2 samples) of a given State.

Metric 1% 1% 4% 4%
1st 200th 1st 200th 1st 200th 1st 200th
Sensitivity 83.3 82.5 81.7 83.3 83.3 83.3 78.3 78.3
Specificity 88.3 87.5 88.3 85.0 88.3 85.0 91.7 86.7
Quality 171.7 170.0 170.0 168.3 171.7 168.3 170.0 165.0

Sensitivity, specificity and quality (sensitivity + specificity) for the best and 200th best medoid classifier algorithm in each of the two runs using 5-, 6-, and 7-peak intensities from the set of 300.  The evolutionary programming search used a population size of 400 and ran for 800 generations with the requirement that there are at most 40 Case-cells and 40 Control-cells.

Metric 5-Features 5-Features 6-Features 6-Features 7-Features 7-Features
1st 200th 1st 200th 1st 200th 1st 200th 1st 200th 1st 200th
Sens 100.0 100.0 90.0 83.3 100.0 100.0 91.7 86.7 100.0 100.0 93.3 90.0
Spec 93.3 81.7 100.0 100.0 93.3 86.7 100.0 100.0 95.0 90.0 100.0 100.0
Quality 193.3 181.7 190.0 183.3 193.3 186.7 191.7 186.7 195.0 190.0 193.3 190.0

(Last updates 4/21/07)