title: Initial points selection for clustering gene expression data: a spatial contiguity analysis-based approach.
abstract: Clustering is considered one of the most powerful tools for analyzing gene expression data. Although clustering has been extensively studied, a problem remains significant: iterative techniques like k-means clustering are especially sensitive to initial starting conditions. An unreasonable selection of initial points leads to problems including local minima and massive computation. In this paper, a spatial contiguity analysis-based approach is proposed, aiming to solve this problem. It employs principal component analysis (PCA) to identify data points that are likely extracted from different clusters as initial points. This helps to avoid local minima, and accelerates the computation. The effectiveness of the proposed approach was validated on several benchmark datasets.
authors.affiliation: College of Automation and Electrical Engineering, Nanjing University of Technology, No. 30, Puzhu South Road, Nanjing 211816, China Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, No. 29, Yudao Sreet, Nanjing 210016, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Yi
authors.affiliation: College of Automation and Electrical Engineering, Nanjing University of Technology, No. 30, Puzhu South Road, Nanjing 211816, China.
authors.forename: Cuimei
authors.initials: C
authors.lastname: Bo
authors.affiliation: Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, No. 29, Yudao Sreet, Nanjing 210016, China.
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Song
authors.affiliation: College of Automation and Electrical Engineering, Nanjing University of Technology, No. 30, Puzhu South Road, Nanjing 211816, China.
authors.forename: Yuhao
authors.initials: Y
authors.lastname: Yuan
mesh_terms: D000465:Algorithms; D000818:Animals; D020869:Gene Expression Profiling / Q000379:methods*; D005810:Multigene Family / Q000235:genetics*; D010363:Pattern Recognition, Automated / Q000379:methods*; D025341:Principal Component Analysis; D020543:Proteome / Q000235:genetics*; D051381:Rats; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D020543:Proteome
keywords: Gene expression data; initial points; k-means; spatial contiguity analysis