Assisted gene expression-based clustering with AWNCut

doi:10.1002/sim.7928

CORC > 上海财经大学 > 上海财经大学

	Assisted gene expression-based clustering with AWNCut
	Li, Yang 1,2; Bie, Ruofan 2; Hidalgo, Sebastian J. Teran 5; Qin, Yichen 4; Wu, Mengyun 3,5; Ma, Shuangge 2,5
刊名	STATISTICS IN MEDICINE
	2018-12-20
卷号	37 期号:29 页码:4386-4403
关键词	assisted analysis clustering gene expression data NCut
ISSN号	0277-6715
DOI	10.1002/sim.7928
英文摘要	In the research on complex diseases, gene expression (GE) data have been extensively used for clustering samples. The clusters so generated can serve as the basis for disease subtype identification, risk stratification, and many other purposes. With the small sample sizes of genetic profiling studies and noisy nature of GE data, clustering analysis results are often unsatisfactory. In the most recent studies, a prominent trend is to conduct multidimensional profiling, which collects data on GEs and their regulators (copy number alterations, microRNAs, methylation, etc.) on the same subjects. With the regulation relationships, regulators contain important information on the properties of GEs. We develop a novel assisted clustering method, which effectively uses regulator information to improve clustering analysis using GE data. To account for the fact that not all GEs are informative, we propose a weighted strategy, where the weights are determined data-dependently and can discriminate informative GEs from noises. The proposed method is built on the NCut technique and effectively realized using a simulated annealing algorithm. Simulations demonstrate that it can well outperform multiple direct competitors. In the analysis of TCGA cutaneous melanoma and lung adenocarcinoma data, biologically sensible findings different from the alternatives are made.
WOS研究方向	Mathematical & Computational Biology ; Public, Environmental & Occupational Health ; Medical Informatics ; Research & Experimental Medicine ; Mathematics
语种	英语
出版者	WILEY
WOS记录号	WOS:000450111600004
内容类型	期刊论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/425]
专题	上海财经大学
作者单位	1.Renmin Univ China, Ctr Appl Stat, Beijing, Peoples R China; 2.Renmin Univ China, Sch Stat, Beijing 100872, Peoples R China; 3.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai 200433, Peoples R China; 4.Univ Cincinnati, Dept Operat Business Analyt & Informat Sys, Cincinnati, OH USA; 5.Yale Univ, Dept Biostat, New Haven, CT 06520 USA
推荐引用方式 GB/T 7714	Li, Yang,Bie, Ruofan,Hidalgo, Sebastian J. Teran,et al. Assisted gene expression-based clustering with AWNCut[J]. STATISTICS IN MEDICINE,2018,37(29):4386-4403.
APA	Li, Yang,Bie, Ruofan,Hidalgo, Sebastian J. Teran,Qin, Yichen,Wu, Mengyun,&Ma, Shuangge.(2018).Assisted gene expression-based clustering with AWNCut.STATISTICS IN MEDICINE,37(29),4386-4403.
MLA	Li, Yang,et al."Assisted gene expression-based clustering with AWNCut".STATISTICS IN MEDICINE 37.29(2018):4386-4403.