gls.series(limma)
gls.series()所属R语言包：limma
Fit Linear Model to Microarray Data by Generalized Least Squares
符合线性模型，广义最小二乘微阵列数据
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Fit a linear model genewise to expression data from a series of microarrays. The fit is by generalized least squares allowing for correlation between duplicate spots or related arrays. This is a utility function for lmFit.
适合线性模型2-6。从一系列微阵列基因表达数据。拟合是通过广义最小二乘平方允许重复斑点或相关阵列之间的相关性。这是一个lmFit的实用功能。
用法----------Usage----------
gls.series(M,design=NULL,ndups=2,spacing=1,block=NULL,correlation=NULL,weights=NULL,...)
参数----------Arguments----------
参数：M
numeric matrix containing log-ratio or log-expression values for a series of microarrays, rows correspond to genes and columns to arrays.
比log或log表达值包含了一系列微阵列的数字矩阵，行对应基因和列数组。
参数：design
numeric design matrix defining the linear model, with rows corresponding to arrays and columns to comparisons to be estimated. The number of rows must match the number of columns of M. Defaults to the unit vector meaning that the arrays are treated as replicates.
数字设计矩阵定义的线性模型，来估计的比较阵列和列相应的行。行数必须匹配M列数。默认的单位向量的含义，阵列被视为重复。
参数：ndups
positive integer giving the number of times each gene is printed on an array. nrow(M) must be divisible by ndups.
正整数，给每一个基因的次数上印有一个数组。 nrow(M)必须ndups整除的。
参数：spacing
the spacing between the rows of M corresponding to duplicate spots, spacing=1 for consecutive spots
M相应的行之间的间距连续点的重复点，spacing=1
参数：block
vector or factor specifying a blocking variable on the arrays. Same length as ncol(M).
向量或指定数组变量阻塞的因素。 ncol(M)的长度相同。
参数：correlation
numeric value specifying the inter-duplicate or inter-block correlation.
数值指定间重复或块间的相关性。
参数：weights
an optional numeric matrix of the same dimension as M containing weights for each spot. If it is of different dimension to M, it will be filled out to the same size.
一个可选的数字矩阵M包含每个点的权重相同的尺寸。如果它不同维度M是，将填写的大小相同。
参数：...
other optional arguments to be passed to dupcor.series.
其他可选参数被传递到dupcor.series。
Details
详情----------Details----------
This is a utility function used by the higher level function lmFit. Most users should not use this function directly but should use lmFit instead.
这是一个实用的功能，更高级别的功能lmFit。大多数用户不应该直接使用此功能，但应该使用lmFit代替。
This function is for fitting gene-wise linear models when some of the expression values are correlated. The correlated groups may arise from replicate spots on the same array (duplicate spots) or from a biological or technical replicate grouping of the arrays. This function is normally called by lmFit and is not normally called directly by users.
这个函数是拟合基因明智的表达式的值时，一些相关的线性模型。相关团体可能会出现在同一阵列（重复点）或从阵列生物技术复制分组的复制点。此功能通常被称为lmFit通常不会由用户直接调用。
Note that the correlation is assumed to be constant across genes. If correlation=NULL then a call is made to duplicateCorrelation to estimated the correlation.
请注意，相关的假设是整个基因不变。如果correlation=NULL然后调用了duplicateCorrelation估计的相关性。
值----------Value----------
A list with components
与组件列表
参数：coefficients
numeric matrix containing the estimated coefficients for each linear model. Same number of rows as M, same number of columns as design.
数字矩阵的每个线性模型的估计系数。 M，design列相同数量相同的行数。
参数：stdev.unscaled
numeric matrix conformal with coef containing the unscaled standard deviations for the coefficient estimators. The standard errors are given by stdev.unscaled * sigma.
数字矩阵形与coef含有非标度系数估计的标准偏差。标准错误stdev.unscaled * sigma。
参数：sigma
numeric vector containing the residual standard deviation for each gene.
数字矢量含有残留的每一个基因的标准偏差。
参数：df.residual
numeric vector giving the degrees of freedom corresponding to sigma
数字向量给予的自由度相应的sigma
参数：correlation
inter-duplicate or inter-block correlation
间重复或块间的相关性
参数：qr
QR decomposition of the generalized linear squares problem, i.e., the decomposition of design standardized by the Choleski-root of the correlation matrix defined by correlation
QR分解的广义线性最小二乘问题，即分解相关矩阵的定义design Choleski根correlation标准化
作者（S）----------Author(s)----------
Gordon Smyth
参见----------See Also----------
duplicateCorrelation.
duplicateCorrelation。
An overview of linear model functions in limma is given by 06.LinearModels.
线性模型功能概述limma由06.LinearModels给出。
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 2012-2-25 23:15:43
