Title :
Partial AUC for Differentiated Gene Detection
Author :
Liu, Zhenqiu ; Hyslop, Terry
Author_Institution :
Greenebaum Cancer Center, Univ. of Maryland, Baltimore, MD, USA
fDate :
May 31 2010-June 3 2010
Abstract :
Partial AUC (pAUC) represents the area with a restricted range of specificity (e.g. low false positive rate). It may identify important regional differentiated genes missed by full-range analysis. Unlike the popular t-test, which is based on the mean difference and the standard deviation between the disease and health groups, pAUC based test statistic relies on the rank of a gene in different samples. It can effectively detect genes that are not significant in a t-test and only differentiated in a subset of the disease groups. Our experiments with real gene expression data show that the proposed pAUC statistic is appealing in terms of both detection power and the biological relevance of the results.
Keywords :
bioinformatics; diseases; genetics; statistical analysis; area under the ROC curve; differentiated gene detection; disease; full-range analysis; health groups; pAUC based test statistic; partial AUC; regional differentiated genes; specificity; Bioinformatics; Biomedical engineering; Cancer detection; Diseases; Gene expression; Neoplasms; Sensitivity; Statistical analysis; Testing; USA Councils; Differentiated Genes; Partial AUC; Specificity;
Conference_Titel :
BioInformatics and BioEngineering (BIBE), 2010 IEEE International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
978-1-4244-7494-3
DOI :
10.1109/BIBE.2010.68