moduleEigengenes(WGCNA)
moduleEigengenes()所属R语言包：WGCNA
Calculate module eigengenes.
计算模块特征基因。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Calculates module eigengenes (1st principal component) of modules in a given single dataset.
计算模块的特征基因（第一主成分），在一个给定的单个数据集的模块。
用法----------Usage----------
moduleEigengenes(expr,
colors,
impute = TRUE,
nPC = 1,
align = "along average",
excludeGrey = FALSE,
grey = ifelse(is.numeric(colors), 0, "grey"),
subHubs = TRUE,
trapErrors = FALSE,
returnValidOnly = trapErrors,
softPower = 6,
scale = TRUE,
verbose = 0, indent = 0)
参数----------Arguments----------
参数：expr
Expression data for a single set in the form of a data frame where rows are samples and columns are genes (probes).
单一的一套数据在一个数据框的行样品和列的形式的表达基因（探针）。
参数：colors
A vector of the same length as the number of probes in expr, giving module color for all probes (genes). Color "grey" is reserved for unassigned genes.
在expr，给模块的颜色数目的探针可用于所有的探针（基因）的长度相同的向量。颜色"grey"保留为未分配的基因。
参数：impute
If TRUE, expression data will be checked for the presence of NA entries and if the latter are present, numerical data will be imputed, using function impute.knn and probes from the same module as the missing datum. The function impute.knn uses a fixed random seed giving repeatable results.
如果TRUE，表达数据进行检查NA项的存在，如果是后者，数值数据进行推算，使用相同的模块中的函数impute.knn和探针丢失的数据。函数impute.knn使用一个固定的随机种子，可重复的结果。
参数：nPC
Number of principal components and variance explained entries to be calculated. Note that only the first principal component is returned; the rest are used only for the calculation of proportion of variance explained. The number of returned variance explained entries is currently min(nPC, 10). If given nPC is greater than 10, a warning is issued.
解释的主要组成部分和方差来计算的项目。请注意，只有第一主成分，则返回，其余的都用唯一的解释方差的比例计算。返回的方差解释条目的数量是目前min(nPC, 10)。如果给定nPC是大于10，则发出一个警告。
参数：align
Controls whether eigengenes, whose orientation is undetermined, should be aligned with average expression (align = "along average", the default) or left as they are (align = ""). Any other value will trigger an error.
控制的特征基因，其方向是不确定的，是否应与平均表达（align = "along average"，默认值），或离开了，因为他们是（align = ""）。任何其他值将触发一个错误。
参数：excludeGrey
Should the improper module consisting of 'grey' genes be excluded from the eigengenes?
不当模块组成的“灰色”基因被排除的特征基因？
参数：grey
Value of colors designating the improper module. Note that if colors is a factor of numbers, the default value will be incorrect.
价值colors指定的不当模块。请注意，如果colors是一个因素的数字，默认值将是不正确的。
参数：subHubs
Controls whether hub genes should be substituted for missing eigengenes. If TRUE, each missing eigengene (i.e., eigengene whose calculation failed and the error was trapped) will be replaced by a weighted average of the most connected hub genes in the corresponding module. If this calculation fails, or if subHubs==FALSE, the value of trapErrors will determine whether the offending module will be removed or whether the function will issue an error and stop.
控制中心基因是否应替代缺失的特征基因。如果TRUE，每个的失踪eigengene（即，eigengene其计算失败，该错误被困住）将取代的加权平均最在相应的模块连接的集线器基因。如果此计算失败，或者如果subHubs==FALSE，trapErrors将决定是否将被删除或有问题的模块的功能是否会发出一个错误，停止。
参数：trapErrors
Controls handling of errors from that may arise when there are too many NA entries in expression data. If TRUE, errors from calling these functions will be trapped without abnormal exit. If FALSE, errors will cause the function to stop. Note, however, that subHubs takes precedence in the sense that if subHubs==TRUE and trapErrors==FALSE, an error will be issued only if both the principal component and the hubgene calculations have failed.
控制处理时可能出现的有太多NA中的表达数据的条目的错误。如果TRUE，调用这些函数的错误将被困无异常退出。如果FALSE，错误会导致停止的功能。但是，请注意，这subHubs的优先级在这个意义上，如果subHubs==TRUE和trapErrors==FALSE，错误将只有发行的主要组分和hubgene的的计算方法都失败了。
参数：returnValidOnly
logical; controls whether the returned data frame of module eigengenes contains columns corresponding only to modules whose eigengenes or hub genes could be calculated correctly (TRUE), or whether the data frame should have columns for each of the input color labels (FALSE).
逻辑控制模块特征基因的返回的数据框是否包含列仅对应的模块，其特征基因或集线器基因可以被正确地计算（TRUE），或数据框是否应该有列，用于每个输入彩色标签（ FALSE“）。
参数：softPower
The power used in soft-thresholding the adjacency matrix. Only used when the hubgene approximation is necessary because the principal component calculation failed. It must be non-negative. The default value should only be changed if there is a clear indication that it leads to incorrect results.
软阈值的邻接矩阵中使用的电力。仅用于时，的hubgene近似是必要的，因为主要成分计算失败。它必须为非负数。只应更改的默认值，如果有一个明显的迹象表明它会导致不正确的结果。
参数：scale
logical; can be used to turn off scaling of the expression data before calculating the singular value decomposition. The scaling should only be turned off if the data has been scaled previously, in which case the function can run a bit faster. Note however that the function first imputes, then scales the expression data in each module. If the expression contain missing data, scaling outside of the function and letting the function impute missing data may lead to slightly different results than if the data is scaled within the function.
逻辑可以用来关闭缩放的表达数据之前计算的奇异值分解。缩放应仅被关闭之前，如果数据已被缩放，在这种情况下，该函数可以更快地运行位。但是请注意，这个函数首先责难，然后秤的表达在每个模块中的数据。如果表达式包含丢失的数据，缩放的功能，并让函数插补缺少的数据可能导致稍微不同的结果，如果数据被缩放函数内的外部。
参数：verbose
Controls verbosity of printed progress messages. 0 means silent, up to (about) 5 the verbosity gradually increases.
控制冗长的印刷进度消息。 0表示沉默，同比增长约5的详细程度逐渐增加。
参数：indent
A single non-negative integer controlling indentation of printed messages. 0 means no indentation, each unit above that adds two spaces.
一个单一的非负整数控制缩进印刷信息。 0表示无压痕，上述各单位，增加了两个空间。
Details
详细信息----------Details----------
Module eigengene is defined as the first principal component of the expression matrix of the corresponding module. The calculation may fail if the expression data has too many missing entries. Handling of such errors is controlled by the arguments subHubs and trapErrors. If subHubs==TRUE, errors in principal component calculation will be trapped and a substitute calculation of hubgenes will be attempted. If this fails as well, behaviour depends on trapErrors: if TRUE, the offending module will be ignored and the return value will allow the user to remove the module from further analysis; if FALSE, the function will stop.
模块eigengene被定义为第一主成分的表达相应的模块的矩阵。如果表达式的数据有太多缺少的项，计算可能会失败。这样的错误处理控制的参数subHubs和trapErrors。如果subHubs==TRUE，主成分计算的错误，将被困住将尝试和替代的hubgenes计算。如果失败，那么，行为取决于trapErrors如果TRUE，有问题的模块将被忽略，并且返回值将允许用户删除的模块，进一步的分析; FALSE ，该功能将停止。
From the user's point of view, setting trapErrors=FALSE ensures that if the function returns normally, there will be a valid eigengene (principal component or hubgene) for each of the input colors. If the user sets trapErrors=TRUE, all calculational (but not input) errors will be trapped, but the user should check the output (see below) to make sure all modules have a valid returned eigengene.
从用户的角度来看，设置trapErrors=FALSE确保，如果函数返回正常，将是一个有效的eigengene（主成分或hubgene）对每个输入的颜色。如果用户设置trapErrors=TRUE，所有calculational的（而不是输入）错误将被困人员，但用户应该检查输出（见下文），以确保所有模块都有一个有效eigengene。
While the principal component calculation can fail even on relatively sound data (it does not take all that many "well-placed" NA to torpedo the calculation), it takes many more irregularities in the data for the hubgene calculation to fail. In fact such a failure signals there likely is something seriously wrong with the data.
虽然主成分的计算可能会失败，即使在比较完善的数据（它并不需要那么多的“占尽天时地利”NA鱼雷计算），它需要更多的违规行为中的数据计算，以hubgene失败的。事实上，这样的故障信号，有可能是严重错误的数据。
值----------Value----------
A list with the following components:
以下组件列表：
参数：eigengenes
Module eigengenes in a dataframe, with each column corresponding to one eigengene. The columns are named by the corresponding color with an "ME" prepended, e.g., MEturquoise etc. If returnValidOnly==FALSE, module eigengenes whose calculation failed have all components set to NA.
模块的特征基因中的数据框，与各列对应的一个eigengene。列被命名为相应的颜色与"ME"前缀，例如，MEturquoise等，如果returnValidOnly==FALSE，模块特征基因，其计算失败的所有组件设置为NA。
参数：averageExpr
If align == "along average", a dataframe containing average normalized expression in each module. The columns are named by the corresponding color with an "AE" prepended, e.g., AEturquoise etc.
如果align == "along average"，一个数据框，在每个模块的平均归一化表达。列被命名为相应的颜色"AE"前缀，例如，AEturquoise等
参数：varExplained
A dataframe in which each column corresponds to a module, with the component varExplained[PC, module] giving the variance of module module explained by the principal component no. PC. The calculation is exact irrespective of the number of computed principal components. At most 10 variance explained values are recorded in this dataframe.
甲数据框，其中每一列对应于一个模块，与组分varExplained[PC, module]给模块的方差module由主成分没有解释。 PC。不论是精确计算的主成分的数目的计算。最多10个方差解释值被记录在这个数据框。
参数：nPC
A copy of the input nPC.
的副本输入nPC。
参数：validMEs
A boolean vector. Each component (corresponding to the columns in data) is TRUE if the corresponding eigengene is valid, and FALSE if it is invalid. Valid eigengenes include both principal components and their hubgene approximations. When returnValidOnly==FALSE, by definition all returned eigengenes are valid and the entries of validMEs are all TRUE.
一个布尔值的向量。每一个组件（对应列在data）TRUE如果相应的eigengene是有效的，和FALSE，如果它是无效的。有效的特征基因本金的组件及其hubgene的的近似。当returnValidOnly==FALSE，定义，所有返回的特征基因的条目是有效的，validMEs都是TRUE。
参数：validColors
A copy of the input colors with entries corresponding to invalid modules set to grey if given, otherwise 0 if colors is numeric and "grey" otherwise.
的的输入颜色与对应的条目无效的模块设置的副本grey如果给定，否则为0colors是数字和“灰色”，否则。
参数：allOK
Boolean flag signalling whether all eigengenes have been calculated correctly, either as principal components or as the hubgene average approximation.
布尔标志的信令，所有特征基因是否已正确计算，无论是作为主要成分，或平均近似的hubgene。
参数：allPC
Boolean flag signalling whether all returned eigengenes are principal components.
布尔标志，信号是否所有返回的特征基因的主要组成部分。
参数：isPC
Boolean vector. Each component (corresponding to the columns in eigengenes) is TRUE if the corresponding eigengene is the first principal component and FALSE if it is the hubgene approximation or is invalid.
布尔向量。每个成分（对应于中的列eigengenes）TRUE如果相应的eigengene是第一主成分和FALSE如果它是hubgene的近似或无效。
参数：isHub
Boolean vector. Each component (corresponding to the columns in eigengenes) is TRUE if the corresponding eigengene is the hubgene approximation and FALSE if it is the first principal component or is invalid.
布尔向量。每个成分（对应于中的列eigengenes）TRUE如果相应的eigengene是的hubgene的近似和FALSE，如果它是第一主成分，或者是无效的。
参数：validAEs
Boolean vector. Each component (corresponding to the columns in eigengenes) is TRUE if the corresponding module average expression is valid.
布尔向量。每个组件（中的列对应eigengenes）TRUE如果相应的模块的平均表达是有效的。
参数：allAEOK
Boolean flag signalling whether all returned module average expressions contain valid data. Note that returnValidOnly==TRUE does not imply allAEOK==TRUE: some invalid average expressions may be returned if their corresponding eigengenes have been calculated correctly.
布尔标志，信号，所有返回的模块平均表达式是否包含有效的数据。请注意这returnValidOnly==TRUE并不意味着allAEOK==TRUE：一些无效的平均表现形式可能会被退回，如果相应的的特征基因已正确计算。
（作者）----------Author(s)----------
Steve Horvath <a href="mailto:SHorvath@mednet.ucla.edu">SHorvath@mednet.ucla.edu</a>, Peter Langfelder
<a href="mailto eter.Langfelder@gmail.com"> eter.Langfelder@gmail.com</a>
参考文献----------References----------
参见----------See Also----------
svd, impute.knn
svd，impute.knn
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。
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发表于 2012-10-1 21:17:09
