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肿瘤微阵列数据统计分析概述

Overview of Statistical Analysis on Cancer Microarray Data
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摘要 微阵列技术已广泛应用于生物学和医学研究领域,如肿瘤的诊断和分型、预测和治疗,理解肿瘤的发生机制、生物学通路和基因网络。统计学方法在这一科学挑战中的地位至关重要。我们综述了微阵列实验数据分析的统计学方法最新发展,主要描述了微阵列数据的标准化、差异表达基因的统计学检验及微阵列技术在肿瘤治疗中的应用,重点介绍了时间序列微阵列数据分析方法和基因调控网络在肿瘤研究中的最新发展。 Microarray techniques have been widely used to monitor gene expression in many areas of biomedi?cal research. Such as the diagnosis and classification, prediction and treatment of tumor, understanding the mecha?nism of tumor, biological pathways and gene networks. Statistical methods are vital for these scientific endeavors.In this article we reviewed recent developments of statistical methods for analyzing data from microarray experiments. Mainly described the standardization of microarray data, statistical tests of differentially expressed genes, and the application of the microarray technology in tumor treatment. Emphasis introduced time series microarray data analy?sis method and the latest development in the study of gene regulatory networks in tumor.
出处 《生物技术通讯》 CAS 2014年第6期875-879,共5页 Letters in Biotechnology
基金 国家自然科学基金(81172770)
关键词 肿瘤 微阵列数据 标准化 差异表达基因 诊断及分型 时间序列 调控网络 tumor microarray data normalization differentially expressed genes classification and clustering time series regulatory network
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  • 1Dudoit S, Yang Y, Callow M J, et al. Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments[J]. Stat Sin, 2002,12:111-139.
  • 2Tseng G C, Oh M K, Rohlin L, et al. Issues in cDNA micro- array analysis: quality filtering, channel normalization, models of variations and assessmentof gene effects[J]. Nucleic Acids Res, 2001,29(12):2549-2557.
  • 3Fan J, Tam P, Vande Woude G, et al. Normalization and analysis of cDNA micro-arrays using within-array replications applied to neuroblastoma cell response to a cytokine[J]. Proc Natl Acad Sci USA, 2004,101(5):1135-1140.
  • 4Fan J, Peng H, Huang T. Semilinear high-dimensional model for normalization of microarray data: a theoretical analysis and partial consistency[J]. J Am Stat Assoc, 2005,100(471): 781-813.
  • 5Huang J, Wang D, Zhang C H. A Two-way semi-linear mod- el for normalization and analysis of cDNA microarray data[J]. J Am Stat Assoc, 2005,100:814-829.
  • 6Ma S, Kosorok M R, Huang J, et al. Robust semiparametric cDNA microarray normalization and significance analysis[J]. Biometrics, 2006,62(2):555-561.
  • 7Cui X, Hwang J T G, Qiu J, et al. Improved statistical tests for differential gene expression by shrinking variance compo- nents estimates[J]. Biostatistics, 2005,6(1):59-75.
  • 8Smyth G K, Michaud J, Scott H S. Use of within-array repli-cate spots for assessing differential expression in microarray experiments[J]. Bioinformatics, 2005,21(9):2067-2075.
  • 9Kerr M K, Churchill G A. Experimental design for gene ex- pression microarrays[J]. Biostatistics, 2001,2(2):183-201.
  • 10Tusher V G, Tibshirani R, Chu G. Significance analysis of mi- croarrays applied to the ionizing radiation response[J]. Proc Natl Acad Sci USA, 2001,98(9):5116-5121.

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