find.a0(siggenes)
find.a0()所属R语言包：siggenes
Computation of the Fudge Factor
福吉因子的计算
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Suggests an optimal value for the fudge factor in an EBAM analysis as proposed by Efron et al. (2001).
为蒙混因素在EBAM分析埃弗龙等人提出的建议最佳值。 （2001年）。
用法----------Usage----------
find.a0(data, cl, method = z.find, B = 100, delta = 0.9,
quan.a0 = (0:5)/5, include.zero = TRUE,
control = find.a0Control(), gene.names = dimnames(data)[[1]],
rand = NA, ...)
参数----------Arguments----------
参数：data
a matrix, data frame or an ExpressionSet object. Each row of data (or exprs(data), respectively) must correspond to a variable (e.g., a gene), and each column to a sample (i.e.\ an observation).
一个矩阵，数据框架或ExpressionSet的对象。 data（或exprs(data)，分别）的每一行必须对应一个变量（例如，一个基因），每个样品的列（即\观察）。
参数：cl
a numeric vector of length ncol(data) containing the class labels of the samples. In the two class paired case, cl can also be a matrix with ncol(data) rows and 2 columns. If data is an ExpressionSet object, cl can also be a character string naming the column of pData(data) 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 = cat.stat, cl should be a vector containing integers between 1 and g, where g is the number of groups. For examples of how cl can be specified, see the manual of siggenes.
一个长度为数字向量ncol(data)样品含有类的标签。在这两个类的配对病例，cl也可以是一个ncol(data)行2列的矩阵。如果data是ExpressionSet的对象，cl也可以是一个字符串，命名列：pData(data)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 = cat.stat，cl应该是一个向量，包含整数1至g，其中g是的组数。对于如何cl可以指定的例子，看到手册siggenes。
参数：method
the name of a function for computing the numerator and the denominator of the test statistic of interest, and for specifying other objects required for the identification of the fudge factor. The default function z.find provides these objects for t- and F-statistics. It is, however, also possible to employ an user-written function. For how to write such a function, see the vignette of siggenes.
一个函数计算感兴趣的检验统计量的分子和分母，并指定蒙混因素的识别所需的其他对象的名称。默认功能z.findT-和F-统计的这些对象。它是，但是，也有可能聘请用户编写的功能。如何写这样的功能，看到插曲siggenes。
参数：B
the number of permutations used in the estimation of the null distribution.
在空分布的估计数排列。
参数：delta
a probability. All genes showing a posterior probability that is larger than or equal to delta are called differentially expressed.
概率。显示所有基因后验概率是大于或等于delta被称为差异表达。
参数：quan.a0
a numeric vector indicating over which quantiles of the standard deviations of the genes the fudge factor a0 should be optimized.
数字矢量表明基因的标准偏差位数蒙混因素a0应优化。
参数：include.zero
should a0 = 0, i.e. the not-modified test statistic also be a possible choice for the fudge factor?
应a0 = 0，即不修改的检验统计量也蒙混因素是可能的选择吗？
参数：control
further arguments for controlling the EBAM analysis with find.a0. For these arguments, see find.a0Control.
为进一步控制与find.a0EBAM分析参数。对于这些参数，请参阅find.a0Control。
参数：gene.names
a character vector of length nrow(data) containing the names of the genes. By default, the row names of data are used.
特征向量的长度nrow(data)包含的基因的名称。默认情况下，data行名称用于。
参数：rand
integer. If specified, i.e. not NA, the random number generator will be set into a reproducible state.
整数。如果指定，即不NA，随机数发生器将被设置成一个可重复的状态。
参数：...
further arguments for the function specified by fun. For further arguments of fun = z.find, see z.find.
进一步为fun指定的函数参数。对于fun = z.find的进一步论据，看到z.find。
Details
详情----------Details----------
The suggested choice for the fudge factor is the value of a0 that leads to the largest number of genes showing a posterior probability larger than delta.
建议选择蒙混因素是a0，呈现出后验概率比delta较大的基因数量最多的价值。
Actually, only the genes having a posterior probability larger than delta are called differentially expressed that do not exhibit a test score less extreme than the score of a gene whose posterior probability is less than delta. So, let's say, we have done an EBAM analysis with a t-test and we have ordered the genes by their t-statistic. Let's further assume that Gene 1 to Gene 5 (i.e. the five genes with the lowest t-statistics), Gene 7 and 8, Gene 3012 to 3020, and Gene 3040 to 3051 are the only genes that show a posterior probability larger than delta. Then, Gene 1 to 5, and 3040 to 3051 are called differentially expressed, but Gene 7 and 8, and 3012 to 3020 are not called differentially expressed, since Gene 6 and Gene 3021 to 3039 show a posterior probability less than delta.
事实上，只有基因有一个后验概率大于delta被称为差异表达不小于基因的后验概率比delta得分的极端表现出测试成绩。所以，让我们说，我们已经做了t检验EBAM分析，我们已经下令其t统计量的基因。让的进一步假设，基因1基因5（即“5的最低牛逼的统计基因），基因7和8，基因3012至3020和基因3040到3051的，显示1后验概率比<大只的基因X>。然后，被称为基因1至5，和3040至3051的差异表达，但不叫差异表达基因7和8，3012到3020，3021到3039显示自6基因和基因后验概率比delta 。
值----------Value----------
An object of class FindA0.
一个类FindA0对象。
注意----------Note----------
The numbers of differentially expressed genes can differ between find.a0 and ebam, even though the same value of the fudge factor is used, since in find.a0 the observed and permuted test scores are monotonically transformed such that the observed scores follow a standard normal distribution (if the test statistic can take both positive and negative values) and an F-distribution (if the test statistic can only take positive values) for each possible choice of the fudge factor.
差异表达基因的数目可以find.a0和ebam，即使使用相同的值蒙混因素，因为在find.a0的观察和置换的考试成绩是单调转化等之间的差异观测到的分数，按照每个可能的选择的软糖因子的标准正态分布（如果检验统计量，可以采取正面和负面的价值观）和F分布（如果检验统计量只能采取正面的价值观）。
作者（S）----------Author(s)----------
Holger Schwender, <a href="mailto:holger.schw@gmx.de">holger.schw@gmx.de</a>
参考文献----------References----------
Empirical Bayes Analysis of a Microarray Experiment, JASA, 96, 1151-1160.
参见----------See Also----------
ebam, FindA0-class, find.a0Control
ebam，FindA0-class，find.a0Control
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
# Obtain the number of differentially expressed genes and the FDR for the[获得差异表达的基因数目和为FDR]
# default set of values for the fudge factor.[蒙混因素值的默认设置。]
find.out <- find.a0(golub, golub.cl, rand = 123)
find.out
# Obtain the number of differentially expressed genes and the FDR when using[使用时，得到的差异表达基因和FDR]
# the t-statistic assuming equal group variances[t-统计假设平等组差异]
find.out2 <- find.a0(golub, golub.cl, var.equal = TRUE, rand = 123)
# Using the Output of the first analysis with find.a0, the number of [首先分析输出，使用与find.a0数量]
# differentially expressed genes and the FDR for other values of[差异表达的基因和其他值FDR]
# delta, e.g., 0.95, can be obtained by[Delta，例如，0.95，可以得到]
print(find.out, 0.95)
# The logit-transformed posterior probabilities can be plotted by[罗吉特转化后验概率可以绘制]
plot(find.out)
# To avoid the logit-transformation, set logit = FALSE.[为了避免罗吉特改造，设置为FALSE的罗吉特。]
plot(find.out, logit = FALSE)
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 14:12:02
