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p-SAGE: 基因集合的参数统计分析方法
引用本文:黄波,李文婷,李雯,夏雪峰,孙之荣.p-SAGE: 基因集合的参数统计分析方法[J].生物化学与生物物理进展,2009,36(11):1415-1422.
作者姓名:黄波  李文婷  李雯  夏雪峰  孙之荣
作者单位:清华大学生物信息与系统生物学研究所,生物信息学教育部重点实验室,生物膜与膜技术国家重点实验室,清华大学生物科学与技术系,北京,100084
基金项目:国家高技术研究发展计划(863)(2006AA020403), 国家重点基础研究发展计划(973)(2009CB918801)和国家自然科学基金(30770498)资助项目
摘    要:肿瘤的发生与发展通常是由重要的细胞通路表达水平的反常导致的.尽管目前已经有很多工作利用基因表达谱数据以及一些其他的先验知识来寻找那些与肿瘤相关的基因集合,但还是没有一个恰当的基因集合的统计学方法.大多数研究都是直接将单基因的检验方法直接应用到基因集合上来.提出了基因集合的参数统计分析方法( p-SAGE ),这个方法应用到大脑肿瘤的实验中,识别了许多显著的基因集合.一些新发现的基因集合是与信号转导和免疫相关的.这个简便有效的方法可以得出有生物学意义的结果.

关 键 词:参数统计分析方法,基因集合,反常基因
收稿时间:2009/5/15 0:00:00
修稿时间:2009/8/25 0:00:00

p-SAGE: Parametric Statistical Analysis of Gene Sets
HUANG Bo,LI Wen-Ting,LI Wen,XIA Xue-Feng and SUN Zhi-Rong.p-SAGE: Parametric Statistical Analysis of Gene Sets[J].Progress In Biochemistry and Biophysics,2009,36(11):1415-1422.
Authors:HUANG Bo  LI Wen-Ting  LI Wen  XIA Xue-Feng and SUN Zhi-Rong
Institution:Institute of Bioinformatics and Systems Biology, MOE Key Laboratory of Bioinformatics, State Key Laboratory of BioMembrane and Membrane Biotechnology, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing 100084, China;Institute of Bioinformatics and Systems Biology, MOE Key Laboratory of Bioinformatics, State Key Laboratory of BioMembrane and Membrane Biotechnology, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing 100084, China;Institute of Bioinformatics and Systems Biology, MOE Key Laboratory of Bioinformatics, State Key Laboratory of BioMembrane and Membrane Biotechnology, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing 100084, China;Institute of Bioinformatics and Systems Biology, MOE Key Laboratory of Bioinformatics, State Key Laboratory of BioMembrane and Membrane Biotechnology, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing 100084, China;Institute of Bioinformatics and Systems Biology, MOE Key Laboratory of Bioinformatics, State Key Laboratory of BioMembrane and Membrane Biotechnology, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing 100084, China
Abstract:Tumor genesis and development often result from deregulation of important biological pathways at the gene expression level. Although there has been much work focused on searching gene sets using gene expression data or other prior information, proper statistical testing of the gene sets is still an open question. Most studies have expanded the testing method of a single gene into the gene sets. Parametric statistical analysis of gene sets ( p-SAGE ) was presented for determining the significant gene sets or pathways associated with a phenotype of interest. The method was applied to brain tumor experiments to identify many gene sets. Some of the newly discovered gene sets were related to signal transduction and immunity. This simple and effective method gives useful biologically meaningful results.
Keywords:parametric statistical method  gene sets  deregulated
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