ExpressionPhenoTest(phenoTest)
ExpressionPhenoTest()所属R语言包：phenoTest
Tests univariate association between a list of phenotype
测试单因素之间的关联表型的列表
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Tests univariate association between a list of phenotype variables and gene expression.
测试单变量型变量和基因表达的列表之间的关联。
用法----------Usage----------
ExpressionPhenoTest(x, vars2test, adjustVars,
p.adjust.method='BH',continuousCategories=3,mc.cores)
参数----------Arguments----------
参数：x
ExpressionSet containing expression levels in exprs(x) and phenotype information in pData(x).
ExpressionSetexprs(x)和pData(x)型信息含表达水平。
参数：vars2test
list with components 'continuous', 'categorical', 'ordinal' and 'survival' indicating which phenotype variables should be tested. 'continuous', 'categorical' and 'ordinal' must be character vectors, 'survival' a matrix with columns named 'time' and 'event'. The names must match names in names(pData(x)).
组件的持续“，”分类“，”序“和”生存“型变量应测试的名单。 “连续”，“类别”和“序”必须是特征向量，“生存”，一个名为“时间”和“事件”的列矩阵。名称中的名称必须符合名称（PDATA（X））。
参数：adjustVars
variables that will be used as adjustment variables when fitting linear models and/or cox models. This variables have to exist in colnames(pData(x)).
将作为调整变量拟合线性模型和/或Cox模型时使用的变量。这个变量有存在colnames(pData(x))的。
参数：p.adjust.method
method for p-value adjustment, passed on to p.adjust. Valid values are c("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none").
P-值调整的方法，通过p.adjust。有效的值是c（“冬青”，“hochberg”，“HOMMEL”，“邦弗朗尼”，“波黑”，“”，“FDR”，“无”）。
参数：continuousCategories
number of categories used for continuous variables.
用于连续变量的类的数量。
参数：mc.cores
the number of cores to use, i.e. how many processes will be spawned (at most).
使用的核心数量，即进程将产生多少（最多）。
Details
详情----------Details----------
The effect of both continuous, categorical and ordinal phenotype variables on gene expression levels are tested via lmFit. For ordinal variables a single coefficient is used to test its effect on gene expression (trend test), which is then used to obtain a P-value (means for each category are reported in the output). Gene expression effects on survival are tested via Cox proportional hazards model, as implemented in function 'coxph'.
基因表达水平的连续，分类和序号表型变量的影响通过lmFit测试。一个单一的系数为序变量用于基因表达（趋势检验），然后用获得的P-值（每个类别的手段，在输出报告），以测试其效果。通过Cox比例风险模型对生存的基因表达的影响进行了测试，在函数coxph“实施。
值----------Value----------
The output is an epheno object, which basically extends an ExpressionSet object. The means, fold changes, standarized hazard ratios and pvalues are stored in the experimentData slot which is accessible with the exprs method. Information about the kind of information of each variable can be found in the phenoData slot which is accessible with the pData method.
输出epheno对象，基本上延伸ExpressionSet对象。存储手段，褶皱的变化，标化的危险比和pvaluesexperimentData槽，这是与exprs方法访问。对每个变量的信息资料，可以发现在phenoData槽，这是与pData方法访问。
There are several methods that can be used to access the information stored in an epheno object. For more information please type one of the following: getFc(x), getHr(x), getMeans(x), getPvals(x), getSummaryDif(x), logFcHr(x), p.adjust.method(x), phenoClass(x), phenoNames(x).
有几种方法可以用来访问在epheno对象存储的信息。如需更多信息，请键入以下之一：getFc(x), getHr(x), getMeans(x), getPvals(x), getSummaryDif(x), logFcHr(x), p.adjust.method(x), phenoClass(x), phenoNames(x)。
作者（S）----------Author(s)----------
David Rossell
举例----------Examples----------
#load eset[加载ESET]
data(eset)
eset
#prepare vars2test[准备vars2test]
survival <- matrix(c("Relapse","Months2Relapse"),ncol=2,byrow=TRUE)
colnames(survival) <- c('event','time')
vars2test <- list(survival=survival)
#run ExpressionPhenoTest[运行ExpressionPhenoTest]
epheno <- ExpressionPhenoTest(eset,vars2test,p.adjust.method='none')
epheno
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-2-26 11:03:55
