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R语言 WGCNA包 simulateDatExpr()函数中文帮助文档(中英文对照)

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发表于 2012-10-1 22:21:35 | 显示全部楼层 |阅读模式
simulateDatExpr(WGCNA)
simulateDatExpr()所属R语言包:WGCNA

                                         Simulation of expression data
                                         表达数据的模拟

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

Simulation of expression data with a customizable modular structure and several different types of noise.
一个可定制的模块化结构和若干不同类型的噪声的表达数据与仿真。


用法----------Usage----------


simulateDatExpr(
  eigengenes,
  nGenes,
  modProportions,
  minCor = 0.3,
  maxCor = 1,
  corPower = 1,
  signed = FALSE,
  propNegativeCor = 0.3,
  geneMeans = NULL,
  backgroundNoise = 0.1,
  leaveOut = NULL,
  nSubmoduleLayers = 0,
  nScatteredModuleLayers = 0,
  averageNGenesInSubmodule = 10,
  averageExprInSubmodule = 0.2,
  submoduleSpacing = 2,
  verbose = 1, indent = 0)



参数----------Arguments----------

参数:eigengenes
a data frame containing the seed eigengenes for the simulated modules. Rows correspond to samples and columns to modules.  
的数据框包含模拟模块的种子特征基因。行对应于样品和列到模块。


参数:nGenes
total number of genes to be simulated.  
总数的基因将被仿真的。


参数:modProportions
a numeric vector with length equal the number of eigengenes in eigengenes plus one, containing fractions of the total number of genes to be put into each of the modules and into the "grey module", which means genes not related to any of the modules. See details.  
一个数值向量的长度等于在eigengenes加一,含有馏分被放入各模块并进入“灰色模块”,基因的总数,这意味着不相关的基因的特征基因的数目任何模块。查看详细信息。


参数:minCor
minimum correlation of module genes with the corresponding eigengene. See details.  
模块的基因与相应的eigengene最小相关。查看详细信息。


参数:maxCor
maximum correlation of module genes with the corresponding eigengene. See details.  
模块的基因与相应的eigengene最大相关。查看详细信息。


参数:corPower
controls the dropoff of gene-eigengene correlation. See details.  
控制空投基因eigengene相关。查看详细信息。


参数:signed
logical: should the genes be simulated as belonging to a signed network? If TRUE, all genes will be simulated to have positive correlation with the eigengene. If FALSE, a proportion given by propNegativeCor will be simulated with negative correlations of the same absolute values.  
逻辑的基因签署的网络模拟?如果TRUE,所有基因将模拟的有正相关的eigengene的。如果FALSE,由propNegativeCor的比例将相同的绝对值呈负相关的模拟。


参数:propNegativeCor
proportion of genes to be simulated with negative gene-eigengene correlations. Only effective if signed is FALSE.  
的基因的比例是模拟具有负的基因eigengene相关的。只有有效的,如果signed是FALSE。


参数:geneMeans
optional vector of length nGenes giving desired mean expression for each gene. If not given, the returned expression profiles will have mean zero.  
可选的矢量的长度nGenes给需要的平均每个基因的表达。如果没有给出,返回的表达谱具有均值为零。


参数:backgroundNoise
amount of background noise to be added to the simulated expression data.  
背景噪声的量被添加到模拟的表达数据。


参数:leaveOut
optional specification of modules that should be left out of the simulation, that is their genes will be simulated as unrelated ("grey"). This can be useful when simulating several sets, in some which a module is present while in others it is absent.  
可选的规格,应留出的模拟模块,这是他们的基因将模拟无关(“灰色”)。这可能是有用的几套模拟时,在其中一个模块存在,而在其他情况下是不存在的。


参数:nSubmoduleLayers
number of layers of ordered submodules to be added. See details.  
要添加的层的排列的子模块的数量。查看详细信息。


参数:nScatteredModuleLayers
number of layers of scattered submodules to be added. See details.  
要添加的层的散射子模块的数量。查看详细信息。


参数:averageNGenesInSubmodule
average number of genes in a submodule. See details.  
平均数的基因中的一个子模块。查看详细信息。


参数:averageExprInSubmodule
average strength of submodule expression vectors.  
子模块表达向量的平均强度。


参数:submoduleSpacing
a number giving submodule spacing: this multiple of the submodule size will lie between the submodule and the next one.   
一些子模块间距:这多个子模块的尺寸将介于子模块下一个。


参数:verbose
integer level of verbosity. Zero means silent, higher values make the output progressively more and more verbose.  
整数的详细程度。零表示沉默,较高的值使输出越来越多,更详细。


参数:indent
indentation for diagnostic messages. Zero means no indentation, each unit adds two spaces.  
缩进诊断消息。零表示无压痕,每个单元增加两个空格。


Details

详细信息----------Details----------

Given eigengenes can be unrelated or they can exhibit non-trivial correlations. Each module is simulated separately from others. The expression profiles are chosen such that their correlations with the eigengene run from just below maxCor to minCor (hence minCor must be between 0 and 1, not including the bounds). The parameter corPower can be chosen to control the behaviour of the simulated correlation with the gene index; values higher than 1 will result in the correlation approaching minCor faster and lower than 1 slower.
由于eigengenes可以无关,或者他们可以表现出不平凡的相关性。每个模块分别是模拟别人的。选择的表达谱使得它们的相关性从正下方的eigengene运行maxCorminCor(因此minCor必须是介于0和1之间,不包括边界)。参数corPower可以选择的行为进行控制的模拟与基因指数的相关性;大于1的值,将导致在相关接近minCor更快和低于1慢。

Numbers of genes in each module are specified (as fractions of the total number of genes nGenes) by modProportions. The last entry in modProportions corresponds to the genes that will be simulated as unrelated to anything else ("grey" genes). The proportion must add up to 1 or less. If the sum is less than one, the remaining genes will be partitioned into groups and simulated to be "close" to the proper modules, that is with small but non-zero correlations (between minCor and 0) with the module eigengene.
在每个模块中的基因的编号所指定(作为基因总数的nGenes)由modProportions的馏分。中的最后一项modProportions对应的基因,这将是模拟无关的任何东西(“灰色”的基因)。必须添加的比例为1或以下。如果总和小于1,其余的基因将被分配到组中,模拟是“接近”的适当的模块,这是与小,但非零的相关性(之间minCor和0)与模块eigengene。

If signed is set FALSE, the correlation for some of the module genes is chosen negative (but the absolute values remain the same as they would be for positively correlated genes). To ensure consistency for simulations of multiple sets, the indices of the negatively correlated genes are fixed and distributed evenly.
如果signed设置FALSE,一些模块基因的相关性选择负(但绝对值仍然是相同的,因为它们可能为正相关的基因)。模拟多套,以确保一致性,指数的负相关的基因是固定的,并均匀地分布。

In addition to the primary module structure, a secondary structure can be optionally simulated. Modules in the secondary structure have sizes chosen from an exponential distribution with mean equal averageNGenesInSubmodule. Expression vectors simulated in the secondary structure are simulated with expected standard deviation chosen from an exponential distribution with mean equal averageExprInSubmodule; the higher this coefficient, the more pronounced will the submodules be in the main modules. The secondary structure can be simulated in several layers; their number is given by SubmoduleLayers. Genes in these submodules are ordered in the same order as in the main modules.
除了主模块结构,二级结构可以任选地模拟。模块的二级结构的大小选择的指数分布,意味着平等averageNGenesInSubmodule。的表达向量中的二级结构的模拟模拟与预期的标准偏差的指数分布意味着选自等于averageExprInSubmodule;这个系数越高,更明显的将子模块中的主模块。在几层的二级结构,可以模拟,其编号由SubmoduleLayers。在这些子模块的基因在主模块以相同的顺序排列的。

In addition to the ordered submodule structure, a scattered submodule structure can be simulated as well. This structure can be viewed as noise that tends to correlate random groups of genes. The size and effect  parameters are the same as for the ordered submodules, and the number of layers added is controlled by nScatteredModuleLayers.
在除了有序的子模块结构,散射的子模块的结构可以被模拟为好。这种结构可以被看作是噪声趋于随机基因组关联。的大小和效果参数是相同的为有序子模块,并添加的层的数量被控制的nScatteredModuleLayers。


值----------Value----------

A list with the following components:
以下组件列表:


参数:datExpr
simulated expression data in a data frame whose columns correspond genes and rows to samples.  
模拟的表达数据的一个数据框中的列对应的样品的基因和行。


参数:setLabels
simulated module assignment. Module labels are numeric, starting from 1. Genes simulated to be outside of proper modules have label 0.  Modules that are left out (specified in leaveOut) are indicated as 0 here.  
模拟模块分配。模块标签的数字,从1开始。模拟是正确的模块之外的基因标签0。被排除在外(指定的模块leaveOut)表示此处为0。


参数:allLabels
simulated module assignment. Genes that belong to leftout modules (specified in leaveOut) are indicated by their would-be  assignment here.  
模拟模块分配。属于leftout模块(leaveOut)表示,他们将被分配在这里指定的基因。


参数:labelOrder
a vector specifying the order in which labels correspond to the given eigengenes, that is labelOrder[1] is the label assigned to module whose seed is eigengenes[, 1] etc.   
一个向量指定的顺序标签对应于给定的特征基因,是labelOrder[1]是标签分配给模块的种子是eigengenes[, 1]等


(作者)----------Author(s)----------


Peter Langfelder



参考文献----------References----------

to the article
modules. BMC Systems Biology 2007, 1:54.
http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/EigengeneNetwork/SupplementSimulations.pdf.

参见----------See Also----------

simulateEigengeneNetwork for a simulation of eigengenes with a given causal structure;
simulateEigengeneNetwork的模拟与给定的因果结构的特征基因;

simulateModule for simulations of individual modules;
simulateModule各个模块的模拟;

simulateDatExpr5Modules for a simplified interface to expression simulations;
simulateDatExpr5Modules的简化表达模拟接口;

simulateMultiExpr for a simulation of several related data sets.
simulateMultiExpr一个模拟的几个相关的数据集。

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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