sam(siggenes)
sam()所属R语言包：siggenes
Significance Analysis of Microarray
芯片的意义分析
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Performs a Significance Analysis of Microarrays (SAM). 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 SAM procedure for categorical data such as SNP data and the possibility to employ an user-written score function.
执行的微阵列（SAM）的意义分析。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，此功能提供了一个分类数据，如SNP数据的可能性，以聘请用户笔试成绩，功能SAM程序。
用法----------Usage----------
sam(data, cl, method = d.stat, control=samControl(),
gene.names = dimnames(data)[[1]], ...)
参数----------Arguments----------
参数：data
a matrix, a 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). Can also be a list (if method = chisq.stat or method = trend.stat). For details on how to specify data in this case, see chisq.stat.
一个矩阵，一个数据框，或ExpressionSet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）。也可以是一个列表（如果method = chisq.stat或method = trend.stat）。对于如何在这种情况下，指定数据的详细信息，请参阅chisq.stat。
参数：cl
a 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. If data is a list, cl needs not to be specified. 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.stat, cl should be a vector containing integers between 1 and g, where g is the number of groups. (In the case of chisq.stat, cl needs not to be specified if data is a list of groupwise matrices.) For examples of how cl can be specified, see the manual of siggenes.
一个长度为向量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。 data如果是一个列表，cl并不需要指定。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.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chisq.stat可以指定的例子，看到的情况下cl，data如果不指定cl是GroupWise的矩阵列表。 siggenes手册。
参数：method
a character string or a name specifying the method/function that should be used in the computation of the expression scores d. If method = d.stat, a modified t-statistic or F-statistic, respectively, will be computed as proposed by Tusher et al. (2001). If method = wilc.stat, a Wilcoxon rank sum statistic or Wilcoxon 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.stat. In this case Pearson's ChiSquare 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.stat can be employed. It is also possible to use an user-written function to compute the expression scores. For details, see Details.
字符串或指定一个名称，应在计算表达式的分数d使用的方法/函数。如果method = d.stat，修改t-统计或F-统计量，分别为，将计算由Tusher等建议。 （2001年）。 method = wilc.stat如果，Wilcoxon秩和统计或Wilcoxon符号秩统计数据将被用来作为表达得分。对于分类数据，如SNP数据分析，method可以设置chisq.stat。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.stat可聘用。它也可以使用用户编写的函数，计算表达式的分数。有关详细信息，请参阅Details。
参数：control
further optional arguments for controlling the SAM analysis. For these arguments, see samControl.
为进一步控制SAM分析可选参数。对于这些参数，请参阅samControl。
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。 data行名称由默认是用。
参数：...
further arguments of the specific SAM methods. If method = d.stat, see the help of d.stat. If method = wilc.stat, see the help of wilc.stat. If method = chisq.stat, see the help of chisq.stat.
具体SAM方法的进一步论据。如果method = d.stat，看到d.stat帮助。如果method = wilc.stat，看到wilc.stat帮助。如果method = chisq.stat，看到chisq.stat帮助。
Details
详情----------Details----------
sam provides SAM procedures for several types of analysis (one and two class analyses with either a modified t-statistic or a Wilcoxon rank statistic, a multiclass analysis with a modified F statistic, and an analysis of categorical data). It is, however, also possible to write your own function for another type of analysis. The required arguments of this function must be data and cl. This function can also have other arguments. The output of this function must be a list containing the following objects:
sam提供了几种类型的分析（之一，两个类别分析，与改造后的T-统计或Wilcoxon秩统计，与修改后的F统计量的多类分析，分类数据分析）SAM程序。它是，但是，也可以写你自己的另一种类型的分析功能。此功能所需的参数必须是data和cl。此功能还可以有其他的参数。这个函数的输出必须是一个列表，其中包含以下对象：
d: a numeric vector consisting of the expression scores of the genes.
d：数字向量的基因表达分数组成。
d.bar: a numeric vector of the same length as na.exclude(d) specifying
d.bar：一个相同长度的数字矢量na.exclude(d)指定
p.value: a numeric vector of the same length as d containing
p.value：一个相同长度的数字向量d包含
vec.false: a numeric vector of the same length as d consisting of the one-sided numbers of falsely called genes, i.e. if d > 0 the numbers of genes expected to be larger than d under the null hypothesis, and if d<0, the number of genes expected to be smaller than d under the
vec.false：数字矢量的长度相同d讹称为基因，即片面的数字，如果d > 0基因的数量预计将大于<X >零假设下，如果d，有望成为下比d<0小的基因数目
s: a numeric vector of the same length as d containing the standard deviations
s：一个相同长度的数字向量d包含的标准偏差
s0: a numeric value specifying the fudge factor. If no fudge factor is calculated,
s0：一个数值，指定蒙混因素。如果没有蒙混因素计算，
mat.samp: a matrix with B rows and ncol(data) columns, where B is the number of permutations, containing the permutations used in the computation of the permuted
mat.samp：B行ncol(data)列，其中B是数排列，包含用于计算的置换排列矩阵
msg: a character string or vector containing information about, e.g., which type of analysis has been performed. msg is printed when the function print or
msg：字符串或向量的信息，例如，已执行哪种类型的分析。功能msg或print印
fold: a numeric vector of the same length as d consisting of the fold
fold：一个相同长度的数字向量d组成的褶皱
If this function is, e.g., called foo, it can be used by setting method = foo in sam. More detailed information and an example will be contained in the siggenes manual.
如果此功能，例如，一个名为foo，它可以通过设置method = foosam。更详细的信息和示例，将载在siggenes手册。
值----------Value----------
An object of class SAM.
类SAM的对象。
作者（S）----------Author(s)----------
Holger Schwender, <a href="mailto:holger.schw@gmx.de">holger.schw@gmx.de</a>
参考文献----------References----------
RNews, 6(5), 45-50.
Categorical Data – SAM and PAM for SNPs. To appear in: Proceedings of the the 28th Annual Conference of the GfKl.
applied to the ionizing radiation response. PNAS, 98, 5116-5121.
参见----------See Also----------
SAM-class,d.stat,wilc.stat, chisq.stat, samControl
SAM-class，d.stat，wilc.stat，chisq.stat，samControl
举例----------Examples----------
# Load the package multtest and the data of Golub et al. (1999)[加载的的包multtest和Golub等数据。 （1999）]
# contained in multtest.[载在multtest。]
library(multtest)
data(golub)
# golub.cl contains the class labels.[golub.cl包含类的标签。]
golub.cl
# Perform a SAM analysis for the two class unpaired case assuming[执行两个类未成的假设情况下的SAM分析]
# unequal variances.[异方差。]
sam.out <- sam(golub, golub.cl, B=100, rand=123)
sam.out
# Obtain the Delta plots for the default set of Deltas[获得默认设置DeltaDelta图]
plot(sam.out)
# Generate the Delta plots for Delta = 0.2, 0.4, 0.6, ..., 2[生成Delta= 0.2，0.4，0.6，...，2Delta图]
plot(sam.out, seq(0.2, 0.4, 2))
# Obtain the SAM plot for Delta = 2[获得SAM的图Delta= 2]
plot(sam.out, 2)
# Get information about the genes called significant using [获取信息有关的基因被称为显著使用]
# Delta = 3.[Delta= 3。]
sam.sum3 <- summary(sam.out, 3, entrez=FALSE)
# Obtain the rows of golub containing the genes called[包含的基因称为获得戈卢布行]
# differentially expressed[差异表达]
sam.sum3@row.sig.genes
# and their names[他们的名字]
golub.gnames[sam.sum3@row.sig.genes, 3]
# The matrix containing the d-values, q-values etc. of the[含有D-值的矩阵，Q值等。]
# differentially expressed genes can be obtained by[可以通过以下方式获得差异表达基因]
sam.sum3@mat.sig
# Perform a SAM analysis using Wilcoxon rank sums[执行SAM分析采用Wilcoxon秩款项]
sam(golub, golub.cl, method="wilc.stat", rand=123)
# Now consider only the first ten columns of the Golub et al. (1999)[现在只考虑Golub等列前十位。 （1999）]
# data set. For now, let's assume the first five columns were[数据集。现在，让我们假设前五列]
# before treatment measurements and the next five columns were[治疗前测量和未来五年列]
# after treatment measurements, where column 1 and 6, column 2[治疗后测量，其中1和6列，第2列]
# and 7, ..., build a pair. In this case, the class labels[7，...，打造一对。在这种情况下，类标签]
# would be[会]
new.cl <- c(-(1:5), 1:5)
new.cl
# and the corresponding SAM analysis for the two-class paired[和相应的SAM分析两个类的配对]
# case would be[情况下会]
sam(golub[,1:10], new.cl, B=100, rand=123)
# Another way of specifying the class labels for the above paired[上述配对指定的类标签的另一种方式]
# analysis is[分析]
mat.cl <- matrix(c(rep(c(-1, 1), e=5), rep(1:5, 2)), 10)
mat.cl
# and the above SAM analysis can also be done by[和上述SAM分析，也可以通过]
sam(golub[,1:10], mat.cl, B=100, rand=123)
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 14:15:03
