PADGE: analysis of heterogeneous patterns of differential gene expression
PADGE: analysis of heterogeneous patterns of differential gene expression
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DOI：
10.1152/physiolgenomics.00259.2006
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发表时间：
2007-12-19
影响因子：
4.6
通讯作者：
Tang, Zhijun
中科院分区：
文献类型：
--
作者：
Li, Li;Chaudhuri, Amitabha;Tang, Zhijun
我们设计了一种新的分析方法，百分位数分析差异基因表达（PADGE），用于确定两组异质性样品之间的差异表达基因。设计PADGE以在一系列百分位数截止值下比较样品亚组的表达谱，并检查随着表达水平增加样品组之间相对表达的趋势。模拟研究表明，PADGE比t-统计、癌症离群值分析（COPA）具有更大的统计功效（Tomlins SA，罗兹DR，Perner S，Dhanasekaran SM，Mehra R，Sun XW，Varambally S，Cao X，Tchinda J，Kuefer R，Lee C，Montie JE，Shah RB，Pienta KJ，Rubin MA，Chinnaiyan AM. Science 310：644 - 648，2005）和峰度（Teschendorff AE，Naderi A，Barbosa-Morais NL，Caldas C. Bioinformatics 22：2269 - 2275，2006）。PADGE在肿瘤组织微阵列数据集的应用证明了其在优先考虑编码潜在治疗靶点或诊断标志物的癌症基因中的实用性。为研究人员开发了一个Web应用程序，用于分析来自异质性生物样品的大型基因表达数据集，并使用PADGE和其他可用方法识别样品类别子集之间的差异表达基因。可用性：www.example.com.
We have devised a novel analysis approach, percentile analysis for differential gene expression (PADGE), for identifying genes differentially expressed between two groups of heterogeneous samples. PADGE was designed to compare expression profiles of sample subgroups at a series of percentile cutoffs and to examine the trend of relative expression between sample groups as expression level increases. Simulation studies showed that PADGE has more statistical power than t-statistics, cancer outlier profile analysis (COPA) (Tomlins SA, Rhodes DR, Perner S, Dhanasekaran SM, Mehra R, Sun XW, Varambally S, Cao X, Tchinda J, Kuefer R, Lee C, Montie JE, Shah RB, Pienta KJ, Rubin MA, Chinnaiyan AM. Science 310: 644-648, 2005), and kurtosis (Teschendorff AE, Naderi A, Barbosa-Morais NL, Caldas C. Bioinformatics 22: 2269-2275, 2006). Application of PADGE to microarray data sets in tumor tissues demonstrated its utility in prioritizing cancer genes encoding potential therapeutic targets or diagnostic markers. A web application was developed for researchers to analyze a large gene expression data set from heterogeneous biological samples and identify differentially expressed genes between subsets of sample classes using PADGE and other available approaches. Availability: http://www.cgl.ucsf.edu/Research/genentech/padge/.