title: Unimodal transform of variables selected by interval segmentation purity for classification tree modeling of high-dimensional microarray data.
abstract: As a greedy search algorithm, classification and regression tree (CART) is easily relapsing into overfitting while modeling microarray gene expression data. A straightforward solution is to filter irrelevant genes via identifying significant ones. Considering some significant genes with multi-modal expression patterns exhibiting systematic difference in within-class samples are difficult to be identified by existing methods, a strategy that unimodal transform of variables selected by interval segmentation purity (UTISP) for CART modeling is proposed. First, significant genes exhibiting varied expression patterns can be properly identified by a variable selection method based on interval segmentation purity. Then, unimodal transform is implemented to offer unimodal featured variables for CART modeling via feature extraction. Because significant genes with complex expression patterns can be properly identified and unimodal feature extracted in advance, this developed strategy potentially improves the performance of CART in combating overfitting or underfitting while modeling microarray data. The developed strategy is demonstrated using two microarray data sets. The results reveal that UTISP-based CART provides superior performance to k-nearest neighbors or CARTs coupled with other gene identifying strategies, indicating UTISP-based CART holds great promise for microarray data analysis.
authors.affiliation: State Key Laboratory of Chemo/Biosensing and Chemometrics, Laboratory of Tobacco Chemistry, College of Chemistry and Chemical Engineering, Hunan University, Changsha, PR China.
authors.forename: Wen
authors.initials: W
authors.lastname: Du
authors.forename: Ting
authors.initials: T
authors.lastname: Gu
authors.forename: Li-Juan
authors.initials: LJ
authors.lastname: Tang
authors.forename: Jian-Hui
authors.initials: JH
authors.lastname: Jiang
authors.forename: Hai-Long
authors.initials: HL
authors.lastname: Wu
authors.forename: Guo-Li
authors.initials: GL
authors.lastname: Shen
authors.forename: Ru-Qin
authors.initials: RQ
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D020869:Gene Expression Profiling; D015973:Gene Expression Regulation, Leukemic; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D015448:Leukemia, B-Cell / Q000235:genetics; D007951:Leukemia, Myeloid / Q000235:genetics; D008228:Lymphoma, Non-Hodgkin / Q000235:genetics; D008957:Models, Genetic; D009447:Neuroblastoma / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000235:genetics; D054218:Precursor T-Cell Lymphoblastic Leukemia-Lymphoma / Q000235:genetics; D012208:Rhabdomyosarcoma / Q000235:genetics; D012512:Sarcoma, Ewing / Q000235:genetics