ebam(siggenes)
ebam()所属R语言包：siggenes
Empirical Bayes Analysis of Microarrays
微阵列的经验Bayes分析
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Performs an Empirical Bayes Analysis of Microarrays (EBAM). It is possible to perform one and two class analyses using either a modified t-statistic or a (standardized) Wilcoxon rank statistic, and a multiclass analysis using a modified F-statistic. Moreover, this function provides a EBAM procedure for categorical data such as SNP data and the possibility to employ an user-written score function.
微阵列（EBAM）执行的经验Bayes分析。它是可以执行一个和两个类别分析，使用改造后的T-统计（标准化）秩统计，多用户使用修改后的F-统计分析。此外，此功能提供了一个EBAM过程分类数据，如SNP数据和聘请用户笔试成绩功能的可能性。
用法----------Usage----------
ebam(x, cl, method = z.ebam, delta = 0.9, which.a0 = NULL,
control = ebamControl(), gene.names = dimnames(x)[[1]],
...)
参数----------Arguments----------
参数：x
either a matrix, a data frame or an ExpressionSet object, or the output of find.a0, i.e.\ an object of class FindA0. Can also be a list (if method = chisq.ebam or method = trend.ebam). For the latter case, see chisq.ebam. If x is not a FindA0 object, then each row of x (or exprs(x), respectively) must correspond to a variable (e.g., a gene or a SNP), and each column to a sample.
无论是一个矩阵，一个数据框或ExpressionSet对象，或输出find.a0，即\一个类的对象FindA0。也可以是一个列表（如果method = chisq.ebam或method = trend.ebam）。对于后一种情况下，看到chisq.ebam。如果x不是FindA0的对象，然后x（或exprs(x)，分别）的每一行必须对应一个变量（例如，一个基因或一个SNP），每列一个样本。
参数：cl
a specification of the class labels of the samples. Ignored if x is a FindA0 object. Needs not to be specified if x is a list. Typically, cl is specified by a vector of length ncol(x). In the two class paired case, cl can also be a matrix with ncol(x) rows and 2 columns. If x is an ExpressionSet object, cl can also be a character string naming the column of pData(x) that contains the class labels of the samples. In the one-class case, cl should be a vector of 1's. In the two class unpaired case, cl should be a vector containing 0's (specifying the samples of, e.g., the control group) and 1's (specifying, e.g., the case group). In the two class paired case, cl can be either a numeric vector or a numeric matrix. If it is a vector, then cl has to consist of the integers between -1 and -n/2 (e.g., before treatment group) and between 1 and n/2 (e.g., after treatment group), where n is the length of cl and k is paired with -k, k=1,…,n/2. If cl is a matrix, one column should contain -1's and 1's specifying, e.g., the before and the after treatment samples, respectively, and the other column should contain integer between 1 and n/2 specifying the n/2 pairs of observations. In the multiclass case and if method = chisq.ebam or method = trend.ebam, cl should be a vector containing integers between 1 and g, where g is the number of groups. In the two latter cases, cl needs not to be specified, if x is a list. For details, see chisq.ebam. For examples of how cl can be specified, see the manual of siggenes.
样品的类标签的规范。忽略x如果是FindA0对象。需要不被指定，如果x是一个列表。通常情况下，cl指定长度ncol(x)向量。在这两个类的配对病例，cl也可以是一个ncol(x)行2列的矩阵。如果x是ExpressionSet的对象，cl也可以是一个字符串，命名列：pData(x)包含的样本类的标签。在一类的情况下，cl应该是1的向量。在两个类未成的情况下，cl应该是一个向量，包含0（指定的，例如，与对照组样品）和1（指定，例如，病例组）。在这两个类的配对病例，cl可以是一个数值向量或数字矩阵。如果它是一个矢量，然后cl-1之间的整数组成-n/2（例如，治疗前组）与1和n/2（例如，治疗后组） ，其中n是cl和k-k，k=1,…,n/2配对的长度。 cl如果是一个矩阵，一列应包含1和1的规定，例如，前和治疗后的样品，分别与其他列应该包含整数1至n/2指定 n/2对观测。在多的情况下，如果method = chisq.ebam或method = trend.ebam，cl应该是一个向量，包含整数1至g，其中g是的组数。在后一种情况下，cl需要不被指定，如果x是一个列表。有关详细信息，请参阅chisq.ebam。对于如何cl可以指定的例子，看到手册siggenes。
参数：method
a character string or name specifying the method or function that should be used in the computation of the expression score z. If method = z.ebam, a modified t- or F-statistic, respectively, will be computed as proposed by Efron et al. (2001). If method = wilc.ebam, a (standardized) Wilcoxon sum / signed rank statistic will be used as expression score. For an analysis of categorical data such as SNP data, method can be set to chisq.ebam. In this case, Pearson's Chi-squared statistic is computed for each row. If the variables are ordinal and a trend test should be applied (e.g., in the two-class case, the Cochran-Armitage trend test), method = trend.ebam can be employed. It is also possible to employ an user-written function for computing an user-specified expression score. For details, see the vignette of siggenes.
字符串或表达得分z的计算应在使用指定的方法或函数的名称。如果method = z.ebam，T-或F-统计量，分别修改，将埃弗龙等人提出的计算。 （2001年）。如果method = wilc.ebam（标准化）秩秩统计量的总和/签名将作为表达得分。对于分类数据，如SNP数据分析，method可以设置chisq.ebam。在这种情况下，Pearson的卡方统计计算每一行。如果变量是序和趋势测试应适用（例如，在两个阶级的情况下，科克伦Armitage趋势检验），method = trend.ebam可聘用。它也有可能聘请为用户编写的函数，计算用户指定的表达得分。有关详情，请参阅插曲siggenes。
参数：delta
a numeric vector consisting of probabilities for which the number of differentially expressed genes and the FDR should be computed, where a gene is called differentially expressed if its posterior probability is larger than Delta.
一个数值向量组成的差异表达基因和FDR应计算概率，其中差异表达的基因被称为后验概率是较大的比Delta。
参数：which.a0
an integer between 1 and the length of quan.a0 of find.a0. If NULL, the suggested choice of find.a0 is used. Ignored if x is a matrix, data frame or ExpressionSet object.
1之间的整数和quan.a0find.a0的长度。如果NULLfind.a0的建议选择使用。被忽略，如果x是一个矩阵，数据框架或ExpressionSet的对象。
参数：control
further arguments for controlling the EBAM analysis. For these arguments, see ebamControl.
进一步控制EBAM分析参数。对于这些参数，请参阅ebamControl。
参数：gene.names
a vector of length nrow(x) specifying the names of the variables. By default, the row names of the matrix / data frame comprised by x are used.
一个长度为向量nrow(x)指定变量的名称。默认情况下，矩阵/数据框的行名x用于组成。
参数：...
further arguments of the specific EBAM methods. If method = z.ebam, see z.ebam. If method = wilc.ebam, see wilc.ebam. If method = chisq.ebam, see chisq.ebam.
的具体EBAM方法的进一步论据。如果method = z.ebam，看到z.ebam。如果method = wilc.ebam，看到wilc.ebam。如果method = chisq.ebam，看到chisq.ebam。
值----------Value----------
An object of class EBAM.
一个类EBAM对象。
作者（S）----------Author(s)----------
Holger Schwender, <a href="mailto:holger.schw@gmx.de">holger.schw@gmx.de</a>
参考文献----------References----------
of a Microarray Experiment. JASA, 96, 1151-1160.
RNews, 6(5), 45-50.
Studies. Proceedings of the National Academy of Sciences, 100, 9440-9445.
参见----------See Also----------
EBAM-class, find.a0, z.ebam,
EBAM-class，find.a0，z.ebam
举例----------Examples----------
# Load the data of Golub et al. (1999) contained in the package multtest.[Golub等装入的数据。 （1999年）载包multtest。]
data(golub)
# golub.cl contains the class labels.[golub.cl包含类的标签。]
golub.cl
# Perform an EBAM analysis for the two class unpaired case assuming[两个类未成的假设情况下执行EBAM分析]
# unequal variances. Specify the fudge factor a0 by the suggested[异方差。建议指定软糖因子A0]
# choice of find.a0[可选择的find.a0]
find.out <- find.a0(golub, golub.cl, rand = 123)
ebam.out <- ebam(find.out)
ebam.out
# Since a0 = 0 leads to the largest number of genes (i.e. the suggested[由于A0 = 0导致的基因数量最多（即建议]
# choice of a0), the following leads to the same results as the above[A0）的选择，以下导致上述相同的结果]
# analysis (but only if the random number generator, i.e. rand, is set[分析（但仅在该随机数发生器，即兰特，设置]
# to the same number).[以相同的号码）。]
ebam.out2 <- ebam(golub, golub.cl, a0 = 0, fast = TRUE, rand = 123)
ebam.out2
# If fast is set to TRUE in ebam, a crude estimate of the number of[如果快速设置为TRUE，数量粗略估计ebam]
# falsely called genes is used (see the help file for z.ebam). This[虚假称为基因（看到帮助z.ebam文件）。这]
# estimate is always employed in find.a0. [估计总是在find.a0就业。]
# The exact number is used in ebam when performing[表演时，确切的数字是用来在ebam]
ebam.out3 <- ebam(golub, golub.cl, a0 = 0, rand = 123)
ebam.out3
# Since this is the recommended way, we use ebam.out3 at the end of[由于这是推荐的方法，我们使用在年底ebam.out3]
# the Examples section for further analyses.[为进一步分析的例子。]
# Perform an EBAM analysis for the two class unpaired case assuming[两个类未成的假设情况下执行EBAM分析]
# equal group variances. Set a0 = 0, and use B = 50 permutations[平等组差异。集A0 = 0，使用B = 50排列]
# of the class labels.[类的标签。]
ebam.out4 <- ebam(golub, golub.cl, a0 = 0, var.equal = TRUE, B = 50,
rand = 123)
ebam.out4
# Perform an EBAM analysis for the two class unpaired cased assuming[执行这两个类未成EBAM分析套管假设]
# unequal group variances. Use the median (i.e. the 50% quantile)[不平等组差异。使用中位数（即50％的分量）]
# of the standard deviations of the genes as fudge factor a0. And[蒙混因素A0基因的标准偏差。和]
# obtain the number of genes and the FDR if a gene is called [获得的基因和FDR的数量，如果一个基因被称为]
# differentially when its posterior probability is larger than[差异时，它的后验概率大于]
# 0.95.[0.95。]
ebam.out5 <- ebam(golub, golub.cl, quan.a0 = 0.5, delta = 0.95,
rand = 123)
ebam.out5
# For the third analysis, obtain the number of differentially[第三分析，获得数差异]
# expressed genes and the FDR if a gene is called differentially[基因表达和FDR，如果一个基因的差异被称为]
# expressed if its posterior probability is larger than 0.8, 0.85,[表示，如果它的后验概率大于0.8，0.85，]
# 0.9, 0.95.[0.9，0.95。]
print(ebam.out3, c(0.8, 0.85, 0.9, 0.95))
# Generate a plot of the posterior probabilities for delta = 0.9.[生成后验概率为δ= 0.9的图。]
plot(ebam.out3, 0.9)
# Obtain the list of genes called differentially expressed if their[获得列表称为差异表达的基因，如果他们]
# posterior probability is larger than 0.99, and gene-specific [后验概率大于0.99，特定基因]
# statistics for these variables such as their z-value and their[这些变量，如z值及其统计]
# local FDR.[当地FDR。]
summary(ebam.out3, 0.99)
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。
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发表于 2012-2-26 14:11:44
