06.LinearModels(limma)
06.LinearModels()所属R语言包：limma
Linear Models for Microarrays
微阵列的线性模型
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This page gives an overview of the LIMMA functions available to fit linear models and to interpret the results. This page covers models for two color arrays in terms of log-ratios or for single-channel arrays in terms of log-intensities. If you wish to fit models to the individual channel log-intensities from two colour arrays, see 07.SingleChannel.
此页面提供的LIMMA功能符合线性模型，并解释结果的概述。这页包括两个log比率或log强度单通道阵列的颜色阵列模式。如果你想以适应模型，登录强度从两种颜色的数组的单个通道，看到07.SingleChannel“。
The core of this package is the fitting of gene-wise linear models to microarray data. The basic idea is to estimate log-ratios between two or more target RNA samples simultaneously. See the LIMMA User's Guide for several case studies.
这个套件的核心是微阵列基因分段线性模型的拟合数据。其基本思路是同时进行两个或两个以上的目标RNA样本数比率之间的估计。几情况例研究参见的LIMMA用户指南。
拟合模型----------Fitting Models----------
The main function for model fitting is lmFit. This is recommended interface for most users. lmFit produces a fitted model object of class MArrayLM containing coefficients, standard errors and residual standard errors for each gene. lmFit calls one of the following three functions to do the actual computations:
模型拟合的主要功能是lmFit。这个建议对于大多数用户界面。 lmFit产生的拟合模型对象类MArrayLM载系数，标准误差和标准误差为每一个基因的残余。 lmFit调用以下三个功能做实际的计算：
Straightforward least squares fitting of a linear model for each gene.
简单的至少平方为每一个基因的线性模型的拟合。
An alternative to lm.series using robust regression as implemented by the rlm function in the MASS package.
一种替代lm.series使用稳健回归实施rlm在大众包的功能。
Generalized least squares taking into account correlations between duplicate spots (i.e., replicate spots on the same array) or related arrays.
广义最小的广场到重复点（即复制点在同一阵列）或相关阵列之间的帐户关联。
All the functions which fit linear models use link{getEAW} to extract data from microarray data objects, and unwrapdups which provides an unified method for handling duplicate spots.
所有的功能，适合线性模型使用link{getEAW}从芯片的数据对象中提取数据，unwrapdups它提供了一个统一的方法处理重复点。
形成了设计矩阵----------Forming the Design Matrix----------
lmFit has two main arguments, the expression data and the design matrix. The design matrix is essentially an indicator matrix which specifies which target RNA samples were applied to each channel on each array. There is considerable freedom in choosing the design matrix - there is always more than one choice which is correct provided it is interpreted correctly.
lmFit有两个主要论点，表达数据和设计矩阵。设计矩阵基本上是指定的目标RNA样品被应用到每个阵列上的每个通道的一个指标矩阵。有相当大的自由选择设计矩阵 - 总是有多个选择，这是正确的，它的正确解释。
Design matrices for Affymetrix or single-color arrays can be created using the function model.matrix which is part of the R base package. The function modelMatrix is provided to assist with creation of an appropriate design matrix for two-color microarray experiments. For direct two-color designs, without a common reference, the design matrix often needs to be created by hand.
Affymetrix公司或单色阵列的设计矩阵可以创建使用功能model.matrix的R基包的一部分。功能modelMatrix提供协助两色微阵列实验，创造一个适当的设计矩阵。直接两色设计，没有一个共同的参考，设计矩阵往往需要手工创建。
利息比较----------Making Comparisons of Interest----------
Once a linear model has been fit using an appropriate design matrix, the command makeContrasts may be used to form a contrast matrix to make comparisons of interest. The fit and the contrast matrix are used by contrasts.fit to compute fold changes and t-statistics for the contrasts of interest. This is a way to compute all possible pairwise comparisons between treatments for example in an experiment which compares many treatments to a common reference.
一次线性模型已适合使用适当的设计矩阵，命令makeContrasts可以用来形成对比矩阵，使比较利益。拟合和对比度矩阵使用contrasts.fit计算倍的变化和利益的反差t-统计。这是一种方法来计算之间的所有可能的治疗，例如成对比较，在实验中比较多的治疗，以一个共同的参考。
评估的差异表达----------Assessing Differential Expression----------
After fitting a linear model, the standard errors are moderated using a simple empirical Bayes model using eBayes or treat. ebayes is an older version of eBayes. A moderated t-statistic and a log-odds of differential expression is computed for each contrast for each gene. treat tests whether log-fold-changes are greater than a threshold rather than merely different to zero.
拟合线性模型后，标准的错误是使用一个简单的经验Bayes模型使用eBayes或treat主持。 ebayes是eBayes的旧版本。一个放缓的t-统计和差异表达的log赔率计算每个每个基因的对比。 treat测试log倍的变化是否大于阈值，而不是仅仅不同为零。
eBayes and eBayes use internal functions squeezeVar, fitFDist, tmixture.matrix and tmixture.vector.
eBayes和eBayes使用内部功能squeezeVar，fitFDist，tmixture.matrix和tmixture.vector。
The function zscoreT is sometimes used for computing z-score equivalents for t-statistics so as to place t-statistics with different degrees of freedom on the same scale. zscoreGamma is used the same way with standard deviations instead of t-statistics. These functions are for research purposes rather than for routine use.
有时用于计算Z-得分为t-统计量等值，从而将与同等规模的不同自由度的t-统计量的函数zscoreT。 zscoreGamma是用同样的方式与标准差，而不是t-统计。这些功能是用于研究目的，而不是常规使用。
总结模型拟合----------Summarizing Model Fits----------
After the above steps the results may be displayed or further processed using:
经过上述步骤的结果，可显示或进一步加工使用：
Presents a list of the genes most likely to be differentially expressed for a given contrast.
提出了最有可能表示对于一个给定的对比差异基因列表。
Presents a list of the genes most likely to be differentially expressed for a given set of contrasts.
提出了最有可能要为给定的一组对比差异表达的基因列表。
Volcano plot of fold change versus the B-statistic for any fitted coefficient.
火山图与任何拟合系数的B-统计倍。
Plots fitted coefficients or log-intensity values for time-course data.
小区安装系数时间当然数据或log强度值。
Writes an MarrayLM object to a file.
到一个文件中写入MarrayLM对象。
For multiple testing functions which operate on linear model fits, see 08.Tests.
对于线性模型拟合运作的多种测试功能，请参阅08.Tests。
选型----------Model Selection----------
selectModel provides a means to choose between alternative linear models using AIC or BIC information criteria.
selectModel提供了一种手段之间做出选择使用替代线性模型的AIC或者BIC的信息标准。
作者（S）----------Author(s)----------
Gordon Smyth
参考文献----------References----------
Statistical Applications in Genetics and Molecular Biology, 3, No. 1, Article 3. http://www.bepress.com/sagmb/vol3/iss1/art3
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
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发表于 2012-2-25 23:08:52
