Sample A: Cover Page of Thesis, Project, or Dissertation Proposal

was determined to consist of 30 ProbeSets, and represents a subset of the original 325
differentially expressed ProbeSets. An additional ProbeSet, 34342_s_at (SPP1), was added
because it was determined to be ‘on’ in the Bhattacharjee adenocarcinoma samples and ‘off’ for
the Bhattacharjee normal patients, resulting in a final candidate list of 31 ProbeSets.
Survival Curves
Survival curves for the osteopontin (SPP1) gene used each of the three value-generating methods
(log-transformed the BaFL values), for the Bhattacharjee experimental data, were generated with
the R maxstat package [16, 17]. The SPP1 ProbeSet intensities were associated with the
supplementary clinical data [3], and are provided in the Supplementary Materials Data folder.
Survival curves plot the survival probability of a patient within a cohort over time [18].
Classifiers and AUC Performance Metrics
The AUC classification performance of these 31 ProbeSets was assessed exactly as described in
Chapter 3, using the linear discriminant analysis (LDA), Random Forest (RF), and k Nearest
Neighbors (kNN) classification algorithms [10-13]. These classification experiments used
random sampling with replacement of both the training and test datasets for 100 permutations
[10]. Having selected these ProbeSets as described above, the values obtained from RMA,
dCHIP and BaFL were used as input to the classifiers and in the results below the outcomes are
compared to those obtained in Chapter 3.
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