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. Author manuscript; available in PMC: 2012 Apr 15.
Published in final edited form as: Cancer Res. 2011 Apr 12;71(8):3009–3017. doi: 10.1158/0008-5472.CAN-10-2510

Figure 1.

Figure 1

Overview of the study design. Proteomic data of two independent studies were examined for top ranking discriminatory features identified by MALDI MS. A signature of 9 features was selected from the intercept of best classifiers from these two previous studies based on their statistical significance with false discovery rate-adjusted p values <0.01 and based on the expert visual confirmation of the characteristics of the peak. To assess the association of the signature with cancer status we first build a model using Rahman et al. 2005 cohort (n=51). The intensity of the signature (9 m/z values) was transformed to MALDI MS score to predict the risk of having lung cancer. The model was then tested in the validation cohort (n=60)