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Measuring and evaluating diagnostic efficiency are important in biomarker discovery and validation. The receiver operating characteristic (ROC) curve is a graphical plot for assessing the performance of a classifier or predictor that can be used to test the sensitivity and specificity of diagnostic biomarkers. In this study, we describe PanelComposer, a web-based software tool that uses statistical results from proteomic expression data and validates biomarker candidates based on ROC curves and the area under the ROC curve (AUC) values using a logistic regression model, and provides an ordered list that includes ROC graphs and AUC values for proteins (individually or in combination). This tool allows users to easily compare and assess the effectiveness and diagnostic efficiency of single or multiprotein biomarker candidates.

  1. Manual.
  2. Sample dataset (example.csv)
Start Panel Compose


This study was supported by a grant from MediStar (A112047 to SKJ), the National Project for Personalized Genomic Medicine (A111218-11 to YKP), the National R&D Program for Cancer Control, Ministry of Health and Welfare (1120200 to YKP) by the Ministry for Health and Welfare, and World Class University (WCU) grant (R31-2008-000-10086-0).


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