ISAModules-class(eisa)
ISAModules-class()所属R语言包：eisa
A set of ISA modules
一组的ISA模块
译者：生物统计家园网 机器人LoveR
描述----------Description----------
An ISAModules object stores the results of one ISA run. It contains a set of biclusters (=modules or transcription modules) and some meta information about the ISA run and the input data.
ISAModules对象存储一个ISA运行的结果。它包含了一套biclusters（=模块或转录模块）和一些有关ISA运行和输入数据的元信息。
用法----------Usage----------
## S4 method for signature 'ISAModules'
dim(x)
## S4 method for signature 'ISAModules'
featureNames(modules)
## S4 method for signature 'ISAModules'
sampleNames(modules)
## S4 method for signature 'ISAModules'
annotation(modules)
## S4 method for signature 'ISAModules'
getOrganism(modules)
## S4 method for signature 'ISAModules'
pData(modules)
## S4 method for signature 'ISAModules'
seedData(modules)
## S4 method for signature 'ISAModules'
runData(modules)
## S4 method for signature 'ISAModules'
featureThreshold(modules, mods)
## S4 method for signature 'ISAModules'
sampleThreshold(modules, mods)
## S4 method for signature 'ISAModules'
length(x)
## S4 method for signature 'ISAModules'
getNoFeatures(modules, mods)
## S4 method for signature 'ISAModules'
getNoSamples(modules, mods)
## S4 method for signature 'ISAModules'
getFeatures(modules, mods)
## S4 method for signature 'ISAModules'
getSamples(modules, mods)
## S4 method for signature 'ISAModules'
getFeatureNames(modules, mods)
## S4 method for signature 'ISAModules'
getSampleNames(modules, mods)
## S4 method for signature 'ISAModules'
getFeatureScores(modules, mods)
## S4 method for signature 'ISAModules'
getSampleScores(modules, mods)
## S4 method for signature 'ISAModules'
getFeatureMatrix(modules, binary = FALSE,
sparse = FALSE, mods)
## S4 method for signature 'ISAModules'
getSampleMatrix(modules, binary = FALSE,
sparse = FALSE, mods)
## S4 method for signature 'ISAModules'
getFullFeatureMatrix(modules, eset, mods)
## S4 method for signature 'ISAModules'
getFullSampleMatrix(modules, eset, mods)
## S4 method for signature 'ISAModules,ANY,ANY'
x[i, j, ..., drop = FALSE]
## S4 method for signature 'ISAModules,ANY,ANY'
x[[i, j, ..., drop = FALSE]]
参数----------Arguments----------
参数：x,modules
An ISAModules object.
ISAModules对象。
参数：mods
An optional numeric index vector for the modules. If given, the information is only returned only for the specified modules.
可选模块的数字索引向量。如果给出的信息是只返回唯一指定的模块。
参数：binary
Logical scalar. Whether to binarize the feature or sample scores.
逻辑标量。无论是二值化功能或样本分数。
参数：sparse
Logical scalar. Whether to return a sparse matrix. The Matrix package is required for sparse matrices.
逻辑标量。是否返回一个稀疏矩阵。 Matrix包是必需的稀疏矩阵。
参数：eset
An ExpressionSet or ISAExpressionSet object. This is needed for calculating the scores of the features/samples that are not in the module. If an ExpressionSet object is supplied, then it is normalised by calling ISANormalize on it.
ExpressionSet或ISAExpressionSet对象。这是需要计算的功能/模块的样品得分。如果ExpressionSet对象提供的，那么它被调用ISANormalize标准化。
参数：i
For "[" an index vector for selecting features (=probes, genes). For "[[" an index vector for selecting modules.
为[）指数选择功能（=探针，基因向量。对于“[[选择模块的索引向量。
参数：j
For "[" an index vector for selecting samples. It is ignored for "[[".
对于“[指数选择样本向量。它被忽略的[[。
参数：...
Additional indexing arguments, they are not used, just ignored.
额外的索引参数，他们都没有用，只是被忽略。
参数：drop
This argument is currently not used, just silently ignored.
这种说法目前没有使用，只是静静地忽略。
Details
详情----------Details----------
An ISAModules object contains a set of biclusters, obtained using one run of the Iterative Signature Algorithm.
ISAModules对象包含使用一个迭代签名算法的运行，取得了biclusters集。
Various operations are defined such an object, here we document all of them, in several groups.
各种操作定义这样一个对象，在这里，我们记录所有的人，在几组。
值----------Value----------
dim returns a numeric vector of length two. featureNames and sampleNames return a character vector. annotation and getOrganism return a character vector of length one. pData returns a data frame.
dim返回一个长度为2的数字向量。 featureNames和sampleNames返回一个特征向量。 annotation和getOrganism返回一个长度为1的特征向量。 pData返回一个数据框。
seedData returns a data frame, see more below. runData returns a named list, see more below. featureThreshold and sampleThreshold return a numeric vector.
seedData返回一个数据框，详见下文。 runData返回一个名为名单，详见下文。 featureThreshold和sampleThreshold返回一个数字的向量。
length returns a numeric scalar. getNoFeatures and getNoSamples return a numeric vector.
length返回一个数字标。 getNoFeatures和getNoSamples返回一个数字的向量。
getFeatures and getSamples return a list of named numeric vectors. getFeatureNames and getSampleNames return a list of character vectors. getFeatureScores and getSampleScores return a list of named numeric vectors. getFeatureMatrix, getSampleMatrix, getFullFeatureMatrix and getFullSampleMatrix return a numeric matrix.
getFeatures和getSamples返回一个列表命名的数字向量。 getFeatureNames和getSampleNames返回一个字符向量的名单。 getFeatureScores和getSampleScores返回一个列表命名的数字向量。 getFeatureMatrix，getSampleMatrix，getFullFeatureMatrix和getFullSampleMatrix返回一个数字矩阵。
信息的输入数据。----------Information about the input data.----------
dim returns the dimension of the input expression matrix, number of features times number of samples.
dim返回输入表达式矩阵尺寸，功能的次数的样本数量。
featureNames returns a character vector, the names of the features in the original input matrix. I.e. in the input was an ExpressionSet for an Affymetrix array, then the Affymetrix probe IDs are returned.
featureNames返回一个字符向量，在原始输入矩阵的特征的名称。即在输入ExpressionSet Affymetrix公司的阵列，然后返回的Affymetrix探针的ID。
sampleNames returns a character vector, the names of the samples in the original expression set.
sampleNames返回一个字符向量，在原始的表达集的样本的名称。
annotation returns a character scalar, the name of the array for the input expression set. More precisely, the annotation slot of the input ExpressionSet is returned, this is the name of the annotation package to use for the ExpressionSet.
annotation返回一个字符标量，数组的输入表达式集的名称。更确切地说，annotation输入ExpressionSet返回的插槽，这是注解包的名称使用ExpressionSet。
getOrganism returns the scientific name of the organism for which the input expression data was measures. This is obtained by loading the annotation package of the input ExpressionSet object, so that must be installed.
getOrganism返回的输入表达数据是措施的有机体的学名。这是获得加载输入ExpressionSet对象，所以必须安装的注解包。
pData returns the phenotypic data attached to the input ExpressionSet object, in a data frame, samples as rows and various phenotypic variables as columns.
pData返回的表型数据输入ExpressionSet对象，在一个数据框，行和列各表型变量的样本。
有关ISA运行的信息----------Information about the ISA run----------
seedData returns information about the modules. Each row of the returned data frame corresponds to one module, the columns are various variables:
seedData返回有关模块的信息。返回的数据框的每一行对应一个模块，列各种变数：
iterations The number of ISA iterations needed to find the module.
迭代的ISA迭代需要找到模块。
oscillation The length of the oscillation cycle for
振荡振荡周期的长度
thr.row The feature (=gene) threshold used for finding the module.
thr.row用于寻找模块的功能（基因）的阈值。
thr.col The sample (=condition) threshold used for finding
thr.col样品（=条件）阈值用于寻找
freq The number of times the module was found. This is always
被发现的次数频率的模块。这始终是
rob The robustness score of the module. See
抢劫模块的鲁棒性得分。见
rob.limit The robustness limit that was used for filtering the modules. As this depends of the feature and sample
rob.limit用于过滤模块的鲁棒性限制。因为这取决于功能和样品
runData returns information about the ISA runs, it is a named list with elements:
runData返回的ISA运行的信息，它是一个元素的命名名单：
annotation The annotation package corresponding to the input
注释输入相应的注释包
organism The scientific name of the organism.
生物体有机体学名。
direction The direction parameter of the ISA. Please
方向direction参数的ISA。请
convergence The method to determine ISA convergence, a character scalar. Please see ISAIterate for
收敛的方法来确定ISA收敛，字符标。请看到ISAIterate
cor.limit Correlation limit for the “cor” convergence criterium, see ISAIterate for
“cor”收敛绕圈，看到ISAIteratecor.limit相关限制
eps Difference limit for the “eps” convergence
EPS“eps”衔接的差异限制
corx Size of the time window for the “corx” convergence criterium, see ISAIterate for
corx的时间窗口的大小“corx”收敛绕圈，看到ISAIterate
maxiter The maximum number of ISA iterations that was
maxiter的ISA迭代的最大数量
oscillation Logical, whether oscillating modules were
逻辑振荡，振荡模块是否
N Numeric scalar, the number of input seeds that were used to
列印数字标量，输入种子数被用来
unique Logical scalar, whether ISAUnique was
独特的逻辑标量，是否ISAUnique是
prenormalize Logical scalar, whether the input data was prenormalized during ISA normalization, see
逻辑标prenormalize，输入的数据是否prenormalized的ISA标准化过程中，请参阅
hasNA Logical scalar, whether the normalized input data
汉斯娜逻辑标量，是否归输入数据
rob.perms Numeric scalar, the number of times the input data
rob.perms数字标量，输入数据的次数
Note that some of these might be missing, i.e. rob.perms is only present if ISAFilterRobust was performed.
请注意，其中一些可能会丢失，即rob.perms是目前唯一的ISAFilterRobust进行。
featureThreshold returns the feature thresholds that were used to find the modules.
featureThreshold返回找到模块的功能，使用阈值。
sampleThreshold returns the sample thresholds that were used to find the modules.
sampleThreshold返回的样品被用来找到模块的阈值。
关于模块的信息----------Information about the modules----------
length returns the number of modules.
length返回的模块数量。
getNoFeatures returns the number of features (=genes) in the input data. The number of features after filtering is returned if the input data was filtered.
getNoFeatures返回在输入数据的功能（基因）的数量。如果输入的数据过滤功能，过滤后返回。
getNoSamples returns the number of samples (=conditions) in the input data.
getNoSamples返回的样本（条件），在输入数据的数量。
检索模块----------Retrieve the modules----------
getFeatures returns the indices of the features included in the modules. It returns a list, with one entry for each module. Each entry contains the indices of the features (=genes) in the corresponding module.
getFeatures返回指数包含的功能模块。它返回一个列表，每个模块的一个条目。每个条目都包含在相应的模块功能（基因）的指标。
getSamples does the same as getFeatures, but for samples.
getSamples做getFeatures相同，但样品。
getFeatureNames is similar to getFeatures, but returns feature names instead of feature indices.
getFeatureNamesgetFeatures，但回报，而不是功能指标的功能名称是类似的。
getSampleNames is similar to getSamples, but returns sample names instead of sample indices.
getSampleNames是getSamples，但回报，而不是样本指数样本名。
getFeatureScores returns the feature scores for the selected modules (all modules by default). It returns a list, with one entry for each module. Each list entry contains the feature scores for one module, in a named numeric vector.
getFeatureScores返回所选模块（默认情况下所有模块）的功能分数。它返回一个列表，每个模块的一个条目。每个列表项包含一个模块的功能分数，在一个名为数字向量。
getSampleScores is similar to getFeatureScores, but for samples and sample scores.
getSampleScores是类似getFeatureScores，但样本及样本分数。
getFeatureMatrix returns feature scores for the specified modules (all modules by default) in a matrix form. The number of rows is the number of features and the number of columns is the number of modules requested. It can optionally binarize the values.
getFeatureMatrix返回具有指定的模块矩阵形式（默认情况下所有模块）的成绩。行数的特点是数量和列数是请求的模块数。它可以选择二值化的值。
getSampleMatrix is similar to getFeatureMatrix, but for sample scores.
getSampleMatrixgetFeatureMatrix，但样品的分数是类似的。
getFullFeatureMatrix is similar to getFeatureMatrix, but is also calculates scores for the features that were not included in the module. For this it performs one ISA iteration and omits the thresholding step. You need to supply the normalized (or the original) expression data to make this possible.
getFullFeatureMatrix是getFeatureMatrix类似，但也是计算分数为那些没有包含的功能模块。为此，它执行一个ISA迭代和省略了阈值的步骤。您需要提供规范化（或原）表达数据，使这成为可能。
getFullSampleMatrix is the same as getFullFeatureMatrix, but for sample scores.
getFullSampleMatrix是getFullFeatureMatrix，但样本分数相同。
索引----------Indexing----------
A couple of indexing operations were defined to make it easier selecting subsets of modules, features or samples from an ISAModules object.
被定义的索引操作，使更容易选择ISAModules对象的模块，功能或样本的子集。
The "[[" double bracket indexing operator can be used with a single index vector to select a subset of modules.
[[双括号索引运算符，可以用一个单一的指数向量选择模块的一个子集。
The "[" single bracket indexing operator can be used to restrict an ISAModules object to a subset of features and/or samples. The first index corresponds to features, the second to samples. Indices can be numeric, logical or character vectors, for the latter feature and sample names are used.
的[单括号索引运算符可以被用来限制ISAModules对象的功能和/或样品的一个子集。第一个索引对应的功能，第二个样品。指数可以是数字，逻辑或特征向量，后者的功能和样品名称使用。
作者（S）----------Author(s)----------
Gabor Csardi <a href="mailto:Gabor.Csardi@unil.ch">Gabor.Csardi@unil.ch</a>
参考文献----------References----------
analysis of large-scale gene expression data Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Mar;67(3 Pt 1):031902. Epub 2003 Mar 11.
参见----------See Also----------
The vignette included in the eisa package.
eisa包中包含的小品文。
举例----------Examples----------
data(ALLModulesSmall)
ALLModulesSmall
length(ALLModulesSmall)
dim(ALLModulesSmall)
annotation(ALLModulesSmall)
getOrganism(ALLModulesSmall)
seedData(ALLModulesSmall)
getNoFeatures(ALLModulesSmall)
getNoSamples(ALLModulesSmall)
getFeatureScores(ALLModulesSmall, 1)[[1]]
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 17:14:30
