Two-variate phenotype-targeted tests for detecting phenotypic biomarkers in cancers. (18th August 2020)

• Record Type: Journal Article
• Authors: Lv, Jinxiong; Tu, Shikui; Xu, Lei
• Is Part Of: International journal of data mining and bioinformatics. Volume 24:Number 1(2020)
• Page Start: 38
• Page End: 57
• Publication Date: 2020-08-18
• Subjects: two-variate phenotype-targeted test -- phenotypic biomarkers -- breast cancer -- lung cancer -- thyroid cancer -- body mass index -- overall survival time -- pathologic stage -- microarray expression data -- RNA-seq expression data; Data mining -- Periodicals; Bioinformatics -- Periodicals; 006.312
• Languages: English
• ISSNs: 1748-5673

Abstract

Detection of cancer-related phenotypic biomarkers is crucial for clinical research. Traditional pipeline consists of two stages, i.e., candidates are first selected to be significantly differentially expressed between tumour-adjacent and tumour conditions, and then later are filtered by Phenotype-Targeted tests (PT tests). Such two-phase process has low-detection power. In this paper, two-variate PT test, which jointly considers tumour-adjacent data and tumour data, is adopted to strengthen the detection power. We conduct a systematic investigation on the three implementations of two-variate PT tests for detecting phenotypic biomarkers in three types of cancers, and provide a practical guideline for the usage of the two-variate PT tests. Experimental analysis indicates that the two-variate PT tests achieve stronger detection power than traditional methods. The tumour-adjacent data provides complementary information to the discriminant analysis, and Fisher discriminant analysis is able to best implement two-variate PT test for detecting phenotypic biomarkers in cancers.