anotaPlotSigGenes(anota)
anotaPlotSigGenes()所属R语言包：anota
Filter and plot genes to visualize/summarize genes that are differentially translated.
过滤和图基因可视化/总结基因差异翻译。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function filters the output from the anotaGetSigGenes function based on many user defined thresholds and flags to generate a summary table and optional per gene plots.
此的功能过滤从anotaGetSigGenes功能的输出，根据许多用户定义的阈值和标志，生成汇总表和可选的每个基因图。
用法----------Usage----------
anotaPlotSigGenes(anotaSigObj, selIds=NULL, selContr=NULL, minSlope=NULL, maxSlope=NULL, slopeP=NULL, minEff=NULL, maxP=NULL, maxPAdj=NULL, maxRvmP=NULL, maxRvmPAdj=NULL, selDeltaPT=NULL, selDeltaP=NULL, sortBy=NULL, performPlot=TRUE, fileName="ANOTA_selected_significant_genes_plot.pdf", geneNames=NULL)
参数----------Arguments----------
参数：anotaSigObj
The output from the anotaGetSigGenes function.
从anotaGetSigGenes函数的输出。
参数：selIds
The function can consider only a subset of the identifiers from the input data set (which can be further filtered) or used for custom plotting of identifiers of interest (leaving all filters as NULL). For custom selection of identifiers, supply a vector of identifiers (row names from the original data set) to be included. Default is NULL i.e. filtering is performed on all identifiers. Minimum length of selIds is currently 2. However, if only one identifier is of interest this identifier can be at position one and two of the supplied vector which will lead to that the data for the identifier of interested will be plotted twice.
该功能可以考虑从输入数据集（可以进一步过滤）或用于自定义绘制的利益标识符（留为NULL的所有过滤器）的唯一标识符的一个子集。标识符的自定义选择，提供一个向量标识符（从原始数据集的行名）被列入。默认值为NULL，即过滤所有标识符。目前最小长度selIds的2。然而，如果只有一个标识符感兴趣的是这个标识符可以在位置之一，提供向量，这将导致感兴趣的标识符的数据将被绘制两次。
参数：selContr
Which contrast should be evaulated during the filtering, sorting and plotting? Descriptions of the contrasts can be found in the output from the anotaGetSigGenes object in the usedContrasts slot. Indicate the contrast by the column number.
这对比应筛选，排序和绘制过程中evaulated？对比说明，可以发现在“输出从在usedContrasts插槽anotaGetSigGenes对象。显示的列数对比。
参数：minSlope
The output can be filtered so that genes whose identified slopes are too small can be excluded. Default is NULL i.e. no filtering based on lower boundary of the slope. To exclude genes with e.g. a slope <(-1) assign -1 to minSlope.
可以过滤输出，因此可以排除基因的确定斜坡太小。即没有过滤基于较低的斜坡边界，默认值为NULL。为了排除基因与例如斜坡<（-1）分配-1到minSlope。
参数：maxSlope
The output can be filtered so that genes whose identified slopes are too large can be excluded. Default is NULL i.e. no filtering based on upper boundary of the slope. To exclude genes with e.g. a slope >2 assign 2 to maxSlope.
可以过滤输出，因此可以排除基因的鉴定斜坡太大。即没有过滤斜坡上边界的基础上，默认是空。为了排除基因与例如斜坡> 2分配2 maxSlope。
参数：slopeP
A p-value for the slope being <0 or >1 is calculated if the estimate for the slope is <0 or >1. This p-value can be used to filter the output based on unrealistic slopes. When set low fewer genes will be disqualified. Default is NULL i.e. no filtering based on slope p-value. We recommend setting slopeP between 0.01 and 0.1 depending on data set characteristics.
一个斜率<0或1> p值的计算方法为斜坡的估计是，如果<0或1。 P-值可以用来过滤基于不切实际的斜坡输出。当设置低少的基因将被取消资格。默认即没有过滤基于斜坡p值是NULL。我们建议设置0.01和0.1之间的slopeP取决于数据集特征。
参数：minEff
The output can be filtered based on minimum effect for inclusion. The value is applied both to negative and positive effects: e.g. a value of 1 will evaluate if the effects are >1 OR <(-1). Default is NULL i.e. no filtering based on effect.
纳入最低效果的基础上，可以过滤输出。值同时适用于积极和消极的影响：如值为1，将评估的影响> 1或<（-1）。默认值是NULL即没有过滤效应。
参数：maxP
The output can be filtered based on raw p-values from the anota analysis without RVM (i.e. smaller compared to assigned value). Default is NULL i.e. no filtering.
根据原料从anota分析p值没有RVM的（即较小的分配值相比），可以过滤输出。默认值是NULL，即没有过滤。
参数：maxPAdj
The output can be filtered based on adjusted p-values from the anota analysis without RVM (i.e. smaller compared to assigned value). The adjustment method that was used when running anotaGetSigGenes will be evaluated. Default is NULL i.e. no filtering.
可以过滤输出的基础上调整从anota分析p值没有RVM的（即较小的分配值相比）。运行anotaGetSigGenes时使用的调整方法是，将进行评估。默认值是NULL，即没有过滤。
参数：maxRvmP
The output can be filtered based on raw p-values from the anota analysis with RVM (i.e. smaller compared to assigned value). Default is NULL i.e. no filtering.
原料anota分析RVM的（即较小的分配值相比）p值的基础上，可以过滤输出。默认值是NULL，即没有过滤。
参数：maxRvmPAdj
The output can be filtered based on adjusted p-values from the anota analysis with RVM (i.e. smaller compared to assigned value). The adjustment method that was used when running anotaGetSigGenes will be evaluated. Default is NULL i.e. no filtering.
调整p值从RVM的（即较小的分配值相比）anota分析的基础上，可以过滤输出。运行anotaGetSigGenes时使用的调整方法是，将进行评估。默认值是NULL，即没有过滤。
参数：selDeltaPT
The output can be filtered based on the mean log2(translational activity data / cytosolic mRNA data) between groups difference. The groups are defined by the selected contrast. Default is NULL i.e. no filtering.
可以过滤输出的基础上平均的log2（转化活动数据/胞浆表达数据）组间差异。由选定的对比组的定义。默认值是NULL，即没有过滤。
参数：selDeltaP
The output can be filtered based on the translational activity data only so that the minimum absolute between groups delta translation is used for gene inclusion. The groups are defined by the selected contrast. Default is NULL i.e. no filtering.
可以过滤输出翻译活动数据的基础上，只有这样，群体之间的最小绝对Delta翻译基因列入。由选定的对比组的定义。默认值是NULL，即没有过滤。
参数：sortBy
The output can be sorted by effect ("Eff"), raw p-value("p") or raw RVM p-value ("apvRvmP"). Default is NULL i.e. no sorting.
可以排序的输出效果（“EFF”），原材料p值（“P”）或原始RVM的P-值（“apvRvmP”）。默认值是NULL，即没有排序。
参数：performPlot
The function can generate a graphical output per gene. Default is TRUE i.e. generate plots.
每个基因的功能，可以生成一个图形输出。默认值是TRUE，即生成图。
参数：fileName
The plots are printed to a file whose file name is given here. Default is "ANOTA_selected_significant_genes_plot.pdf".
打印到文件的文件名称是这里给出的图。默认是“ANOTA_selected_significant_genes_plot.pdf”。
参数：geneNames
When anotaPlotSigGenes plots the individual gene plots they will be named by the original row names supplied to the anotaGetSigGenes function. geneNames allows the user to add additional names when plotting to e.g. include gene symbols. Input is a matrix with one column where the original row names match the row names of the input matrix and the desired new names are given in column 1. Default is NULL i.e. no additional names.
当图anotaPlotSigGenes个人基因图，它们将被命名为原行提供的anotaGetSigGenes函数的名称。 geneNames允许用户添加其他的名字时，图到如包括基因符号。输入是一个原始行名称匹配的输入矩阵的行所需的新名称，在第1列的名称和一列的矩阵。默认值为NULL即没有额外的名称。
Details
详情----------Details----------
This function allows the user to filter the output generated from the anotaGetSigGenes function to derive a reduced selection of genes that are considered for further evaluation. This is done by setting one or several of the filtering parameters described above. The function also generates a graphical output which helps when evaluating a single gene's regulation. In the graphical output, the results for each gene is displayed on separate rows. The first graph shows all samples and per sample class regression lines using the common slope with different colors for each sample class. The magnitude of the common slope is indicated. The second graph shows key statistics for the gene without the RVM model for all contrasts analyzed when running anotaGetSigGenes but any ordering and selection of genes is performed on the contrast given by the selContr argument as described above. The third graph is similar to the second but with RVM statistics instead (if RVM was used in the anotaGetSigGenes analysis).
此功能允许用户筛选获得减少选择的基因，为进一步评估认为从anotaGetSigGenes产生的输出功能。这是通过设置上述过滤参数中的一个或多个。在功能上也产生一个图形输出，这有助于进行评估时，单个基因的调控。在图形输出，每个基因的结果显示在单独的行。第一张图显示所有样品，每个样品类回归线，用不同颜色的每个样品类的共同斜坡。表示共同坡度的大小。第二幅图显示无基因的关键统计数据，所有的对比分析运行时，但任何顺序和基因选择如上所述由selContr参数的对比进行anotaGetSigGenes RVM的模型。第三图是类似第二，但与RVM的统计数据，而不是（RVM的，如果是用于在anotaGetSigGenes分析）。
值----------Value----------
anotaPlotSigGenes generates a graphical output as described above and a list object containing summary data for those genes that passed the selected set of filters. The output list object contains the following slots:
anotaPlotSigGenes如上所述生成一个图形输出和一个列表对象包含选定的过滤器，通过这些基因的汇总数据。输出列表对象包含以下插槽：
参数：selectedData
A matrix containing non-RVM data for the filtered identifiers. 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).
矩阵过滤标识符非RVM的数据。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：selectedRvmData
A matrix containing RVM data for the filtered identifiers. 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).
过滤标识符包含RVM的数据矩阵。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：groupIntercepts
A matrix with the group intercepts, i.e. the translational activity for each group independent of cytosolic mRNA level. Can be used for e.g. clustering of translational activity. Data for all groups defined when using the anotaGetSigGenes function are supplied although the filtering is based on the contrast defined under the selContr argument.
一组拦截的矩阵，即每个组独立于单元质中的mRNA水平的翻译活动。可以使用的，例如聚类平移活动。提供使用anotaGetSigGenes函数时定义的所有组的数据，虽然过滤根据定义下selContr参数的对比。
参数：deltaData
Mean delta translational activity data ("deltaP"), mean delta cytosolic mRNA data ("deltaT") and mean delta log ratio data ("deltaPT") comparing the sample classes specified by the selected contrast.
平均Delta转化活动数据（“deltaP”）平均Delta胞质基因数据（的“deltaT”），意味着Delta的log比例比较选定的对比样品由指定的类的数据（的“deltaPT”）。
参数：usedThresholds
A list object with the user set values for the filtering.
与过滤用户设定值列表对象。
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, anotaResidOutlierTestanotaGetSigGenes
anotaPerformQc，的anotaResidOutlierTest“anotaGetSigGenes
举例----------Examples----------
## Load the library and dataset (two phenotypes)[＃加载库和数据集（两个表型）]
library(anota)
data(anotaDataSet)
## Quality control of the data set.[＃数据集的质量控制。]
anotaQcOut <- anotaPerformQc(dataT= anotaDataT[1:200,], dataP=anotaDataP[1:200,],
phenoVec=anotaPhenoVec, nDfbSimData=500)
##Test normality of residuals[＃测试正常残差]
anotaResidOut <- anotaResidOutlierTest(anotaQcObj=anotaQcOut)
##Identify differentially translated genes.[＃确定基因差异翻译。]
anotaSigGeneOut <- anotaGetSigGenes(dataT= anotaDataT[1:200,],
dataP=anotaDataP[1:200,], phenoVec=anotaPhenoVec, anotaQcObj=anotaQcOut)
##Plot some of the differentially expressed mRNAs[＃绘制一些差异表达的基因]
anotSigGeneOutFiltered <-
anotaPlotSigGenes(anotaSigObj=anotaSigGeneOut, selContr=1,
maxP=0.05,slopeP=0.05, maxSlope=1.5, minSlope=(-0.5), selDeltaPT=0.5)
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 12:01:34
