anotaGetSigGenes(anota)
anotaGetSigGenes()所属R语言包：anota
Identify genes that are under translational control independent of cytosolic mRNA levels
识别平移控制下独立于单元质中的mRNA水平的基因
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function uses analysis of partial variance (APV) to identify genes that are under translational regulation independent of cytosolic mRNA levels.
此功能使用部分方差（APV）的分析，以确定基因翻译调控下，独立于单元质中的mRNA水平。
用法----------Usage----------
anotaGetSigGenes(dataT=NULL, dataP=NULL, phenoVec=NULL, anotaQcObj=NULL,
correctionMethod="BH", contrasts=NULL, useRVM=TRUE, useProgBar=TRUE)
参数----------Arguments----------
参数：dataT
A matrix with cytosolic mRNA data. Non numerical rownames are needed.
与单元内的表达数据矩阵。非数值rownames需要。
参数：dataP
A matrix with translational activity data. Non numerical rownames are needed.
翻译活动数据矩阵。非数值rownames需要。
参数：phenoVec
A vector describing the sample classes (each class should have a unique identifier). Note that dataT, dataP and phenoVec have to have the same sample order so that column 1 in dataP is the translational data for a sample, column 1 in dataT is the cytosolic mRNA data and position 1 in phenoVec describes the sample class.
一个向量描述样本类（每类应该有一个唯一的标识符）。请注意，dataT，从datap和phenoVec的必须有相同的看样订货，使列从datap 1是平移的数据为样本，列dataT 1是单元质中的mRNA的数据和位置phenoVec 1描述了样本类。
参数：anotaQcObj
The object returned by anotaPerformQc.
对象返回anotaPerformQc。
参数：correctionMethod
anota corrects p-values for multiple testing using the multtest package. Correction method can be "Bonferroni", "Holm", "Hochberg", "SidakSS", "SidakSD", "BH", "BY", "ABH" or "TSBH" as implemented in the multtest package or "qvalue" as implemented in the qvalue package. Default is "BH".
多个测试使用的multtest包anota纠正的p值。纠正的方法可以是“邦弗朗尼”，“霍尔姆”，“Hochberg”，“SidakSS”，“SidakSD”，“波黑”，“靠”，“陆地棉”或“TSBH”实施在multtest包或的“qvalue”作为在qvalue包实施。默认是“波黑”。
参数：contrasts
When there is more than 2 sample categories it is possible to use custom contrasts. The order of the sample classes needs to be correct and can be seen in the object generated from anotaPerformQc in the phenoClasses slot (see details section).
时有超过2个样本类别，它是可以使用自定义的对比。样本类的顺序是正确的，可以看到生成从的phenoClasses插槽anotaPerformQc对象（见详图）。
参数：useRVM
Should the Random Variance Model be applied. Default is TRUE.
应适用于随机方差模型。默认值是TRUE。
参数：useProgBar
Should the progress bar be shown. Default is TRUE, show progress bar.
应该显示进度条。默认值为true，显示进度栏。
Details
详情----------Details----------
The function performs APV on two or more sample categories. When more than two sample classes are compared it is possible to set custom contrasts to compare the sample classes of interest. Otherwise "treatment" contrasts are used which follow the alphabetical order of the sample classes. The order of the sample classes which the contrast matrix should follow can be found in the output of the anotaPerformQc function in the phenoClasses slot. Contrasts are supplied as a matrix where the sample classes are rows (same order as phenoClasses) and the columns are the different contrasts used. Contrasts are coded by using e.g. -1 for group a, 0 for group b and 1 for group c to compare group a and c; -2 for group a, 1 for group b and 1 for group c to compare group a to b & c. Each column of the contrast matrix should sum to 0 and to analyze orthagonal contrasts the products of all pairwise rows should sum to 0. The results will follow the order of the contrasts, i.e. the anocovaStats slot in the output object is a list with positions 1...n where 1 is the first contrast and n is the last.
函数执行两个或两个以上的样本类别的波动。当两个以上的样本类相比，它可以设置自定义的对比，比较感兴趣的样品类。否则，“治疗”的对比使用，按照字母顺序的样品类。应遵循的对比矩阵的示例类的顺序，可以发现输出在phenoClasses插槽anotaPerformQc功能。对比提供作为基质，样品类是行（如phenoClasses顺序相同）和列是使用不同的对比。对比使用，例如编码-1 A组0，B组和C组1比较，A组和C; C组，A组-2，1比较A组B＆C组和B组1。对比矩阵的每一列应该总结为0，分析orthagonal对比所有成对行的产品应该总结为0。其结果将遵循对比的顺序，在输出对象即anocovaStats插槽位置1 ... n，其中1是第一个对比和n是最后名单。
A rare error can occur when data within dataT or dataP from any gene and any sample class has no variance. This is reported as "ANOVA F-TEST on essentially perfect fit...". In this case those genes that show no variance for a sample class within either dataT or dataP need to be removed before analysis. Trying a different normalization method may fix the problem.
一种罕见的错误可能会发生任何基因和任何样品类当内dataT或从datap数据有没有差异。这是作为“变异数分析F-试验基本上是完美的结合......”报告。在这种情况下，显示这些基因，内无论是dataT或从datap没有一个样本类的方差分析前需要删除。尝试不同的标准化方法可以解决这个问题。
值----------Value----------
anotaGetSigGenes creates a plot showing the fit of the inverse gamma distribution used in RVM (similar output as from anotaPerformQc). anotaGetSigGenes also returns a list object with the following slots:
anotaGetSigGenes创建显示在RVM的（从anotaPerformQc类似的输出）使用的反伽玛分布拟合的图。 anotaGetSigGenes也返回一个列表对象，与下面的插槽：
参数：apvStats
A list object (each slot named from 1 to the number of contrasts) where each slot contains a matrix with statistics from the applied APV for that contrast. Columns are "apvSlope" (the common slope used in APV); "apvSlopeP" (if the slope is <0 or >1 a p-value for the slope being <0 or >1 is calculated; if the slope is >=0 & <=1 this value is set to 1); "unadjustedResidError" (the residual error before calculating the effective residual error); "apvEff" (the group effect); "apvMSerror" (the effective mean square error); "apvF" (the F-value); "residDf" (the residual degrees of freedom); "apvP" (the p-value); "apvPAdj" (the adjusted p-value).
一个List对象（名为对比数从1到每个插槽），每个时隙包含一个矩阵的应用，相反波动的统计。列是的“apvSlope”（共同在APV的斜坡）;“apvSlopeP”（如果坡度<0或> 1，p值<0或> 1计算的斜坡;坡度> = 0＆<= 1这个值设置为1）;“unadjustedResidError”（前有效的残差计算残差）;的“apvEff”（群体效应）;“apvMSerror” ;（有效的均方误差）;“apvF”（F值）;的“residDf”（自由的剩余度）;的“apvP”（p值）;“apvPAdj”（调整p值）。
参数：apvStatsRvm
A summary list object (each slot named from 1 to the number of contrasts) where each slot contains a matrix with RVM statistics from the applied APV. Columns are "apvSlope" (the common slope used in APV); "apvSlopeP" (if the slope is <0 or >1 a p-value for the slope being <0 or >1 is calculated; if the slope is >=0 & <=1 this value is set to 1); "apvEff" (the group effect); "apvRvmMSerror" (the effective mean square error after RVM); "apvRvmF" (the RVM F-value); "residRvmDf" (the residual degrees of freedom after RVM); "apvRvmP" (the RVM p-value); "apvRvmPAdj" (the adjusted RVM p-value).
汇总列表对象（名为对比数从1到每个插槽），每个时隙包含一个从应用APV的RVM的统计矩阵。列是的“apvSlope”（共同在APV的斜坡）;“apvSlopeP”（如果坡度<0或> 1，p值<0或> 1计算的斜坡;坡度> = 0＆<= 1这个值设置为1）;“apvEff”（组效果）;的“apvRvmMSerror”（RVM的有效平均后，方误差）;“apvRvmF”（ RVM的F值）;“residRvmDf”（RVM的自由后的剩余度）;的“apvRvmP”（RVM的p值）;“apvRvmPAdj”（调整后的RVM的p值）。
参数：correctionMethod
The multiple testing correction method used to adjust the p-values.
多个测试校正方法用于调整p值。
参数：usedContrasts
A matrix with the contrasts used. Order is same as in the statistical outputs (column wise) so that the first contrast is found in the first slot of the apvStats and the apvStatsRvm lists.
与使用对比的矩阵。在统计产出（列明智）使对比，发现在第一个插槽，的apvStats，apvStatsRvm名单顺序是相同。
参数：abList
A list object containing the a and b parameters from the inverse gamma fits. Same order as the contrasts.
列表对象，其中包含从A和B的参数逆伽玛适合。顺序相同的对比。
作者（S）----------Author(s)----------
Ola Larsson <a href="mailto la.larsson@ki.se">ola.larsson@ki.se</a>, Nahum Sonenberg
<a href="mailto:nahum.sonenberg@mcgill.ca">nahum.sonenberg@mcgill.ca</a>, Robert Nadon <a href="mailto:robert.nadon@mcgill.ca">robert.nadon@mcgill.ca</a>
参见----------See Also----------
anotaPerformQc,
anotaPerformQc
举例----------Examples----------
## See example for \code{\link{anotaPlotSigGenes}}[＃请参阅\代码例如{\链接{anotaPlotSigGenes}的}]
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 12:01:18
