idFeaturesByBackgating(flowStats)
idFeaturesByBackgating()所属R语言包：flowStats
(Internal use only) Identify features of flow cytometry data using
（仅供内部使用）确定流式单元仪数据的功能，使用
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Identify and labeling significant features using divisive clustering method such as diana.
识别和标记使用diana分裂的聚类分析方法的显着的特点。
用法----------Usage----------
idFeaturesByBackgating(bg, nDim, thres.sigma=2.5, lambda=0.1,
reference.method="median",
plot.workflow=FALSE, ask=names(dev.cur())!="pdf")
参数----------Arguments----------
参数：bg
A data frame containing subpopulations on channels of interests. Must be a returning result from flowStats:::backGating
数据框含有亚利益的渠道。必须从flowStats:::backGating返回结果
参数：nDim
An integer indicating the length of channels of interest.
一个整数，指示的利益渠道的长度。
参数：thres.sigma
An numerical value indicating the threshold at which to cut tree, e.g., as resulting from 'diana', into several clusters.
一个数值表示的阈值，削减树，例如，从“戴安娜”成几个聚类，。
参数：lambda
A numerical value indicating the percentage of the potential features that is used as a threshold for deciding outlier clusters. The default value is 0.1.
一个数值表示百分比的潜在功能，作为一个决定离聚类群的阈值。默认值是0.1。
参数：reference.method
A character vector indicating the method for computing the reference features. If median, the reference feature is defined by the medain of eac cluster of features. Valid methods include median and mean only.
一个特征向量表示方法计算参考功能。如果median，引用功能被定义由EAC聚类功能medain。有效的方法，包括median和mean只。
参数：plot.workflow
Logical. If TURE, display the workflow of feature identification.
逻辑。如果TURE，显示功能鉴定的工作流程。
参数：ask
Logical. If TRUE, the display operates in interactive mode.
逻辑。如果为TRUE，则显示在交互模式下运行。
Details
详情----------Details----------
Using the resulting data frame from backGating as potential features, the algorithm follows four major steps: (i) centering the potential features, which yields the returning value TransMatrix, (ii) using diana to compute a clustering of the potential features, (iii) cutting the tree into several clusters, and (iv) accessing outliers and rendering the final registered features with labels.
使用所产生的数据框从backGating作为潜在的功能，算法如下四个主要步骤：（一）围绕潜在的功能，它产生的返回值TransMatrix，（ii）使用diana计算聚类的潜在功能，（三）切分成几个聚类树，（四）访问异常和渲染标签的最终注册功能。
In step three, the threshold for cutting the tree is computed by
在第三步，计算切割树的阈值
where sd is the standard deviation of the distribution of the height between entities computed by diana.
sd之间的高度计算diana的实体分布的标准偏差。
A cluster is determined as an outlier if the number of its members is less than the median of the numbers of all clusters' members times 'lambda'.
聚类被确定为离群，如果其成员数目少于所有聚类成员次拉姆达的数字位数。
值----------Value----------
参数：register
A list containing registered features for each sample.
一个列表，其中包含每个样品的注册功能。
作者（S）----------Author(s)----------
Chao-Jen Wong
参见----------See Also----------
diana, BackGating, gpaSet.
diana，BackGating，gpaSet。
举例----------Examples----------
## Not run: [＃无法运行：]
data(ITN)
wf <- workFlow(ITN)
tl <- transformList(colnames(ITN)[3:7], asinh, transformationId="asinh")
dat <- trnasformList(ITN, tl)
bg <- backGating(dat, xy=c("FSC", "SSC"), channels="CD3")
## End(Not run)[＃结束（不运行）]
data(BackGating)
results <- flowStats:::idFeaturesByBackgating(bg=BackGating, nDim=2,
plot.workflow=TRUE, ask=TRUE)
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。
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发表于 2012-2-25 18:09:56
