tmixFilter(flowClust)
tmixFilter()所属R语言包：flowClust
Creating Filters and Filtering Flow Cytometry Data
创建过滤器和过滤流式单元仪数据
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The tmixFilter function creates a filter object which is then passed to the filter method that performs filtering on a flowFrame object. This method pair is provided to let flowClust integrate with the flowCore package.
tmixFilter函数创建一个过滤器对象，然后将其传递给filter方法执行过滤flowFrame对象上。这种方法对提供让flowClustflowCore包集成。
用法----------Usage----------
tmixFilter(filterId="tmixFilter", parameters="", ...)
参数----------Arguments----------
参数：filterId
A character string that identifies the filter created.
过滤器创建一个字符串标识。
参数：parameters
A character vector specifying the variables to be used in filtering. When it is left unspecified, all the variables of the flowFrame object are used when running filter. Note that its content will be passed to the varNames argument of flowClust when running filter.
指定要使用的变量在过滤的字符向量。当它被指定，使用flowFrame对象的所有变量，运行时filter。请注意，其内容将被传递到运行时varNamesflowClustfilter参数。
参数：...
Other arguments passed to the flowClust function when running filter, namely, expName, K, B, tol, nu, lambda, nu.est, trans, min.count, max.count, min, max, level, u.cutoff, z.cutoff, randomStart, B.init, tol.init, seed and criterion. All arguments are optional except K that specifies the number of clusters.
其他参数传递给运行时flowClust，即filter，expName，K，B，tolnu函数lambda，nu.est，trans，min.count，max.count，min，max，level， u.cutoff，z.cutoff，randomStart，B.init，tol.init，seed和criterion。所有参数都是可选的，除了K指定聚类。
值----------Value----------
The tmixFilter function returns an object of class tmixFilter that stores all the settings required for performing the filter operations.
tmixFilter函数返回一个对象类tmixFilter存储执行filter操作所需的所有设置。
The filter method is defined in package flowCore and returns an object of class tmixFilterResult (or tmixFilterResultList if
包filter的flowCore方法被定义，并返回一个对象的类tmixFilterResult（或tmixFilterResultList如果
注意----------Note----------
The tmixFilter function returns an object of class tmixFilter that extends the virtual parent filter class in the flowCore package. Hence, the filter operators, namely, &, |, ! and %subset%, also work for the tmixFilter class.
tmixFilter函数返回一个类的对象tmixFilter扩展虚拟父filter类flowCore包。因此，过滤器的运营商，即“&，|，!和%subset%，也可以tmixFilter类。
If filter@K is of length 1, the filter method returns an object of class tmixFilterResult. This class extends both the multipleFilterResult class (in the flowCore package) and the flowClust class. Operations defined for the multipleFilterResult class, like %in%, Subset and split, also work for the tmixFilterResult class. Likewise, methods or functions designed to retrieve filtering (clustering) information from a flowClust object can also be applied on a tmixFilterResult object. These include criterion, ruleOutliers, ruleOutliers<-, Map, posterior, importance, uncertainty and getEstimates. Various functionalities for plotting the filtering results are also available (see the links below).
filter@K如果长度为1的是，filter方法返回一个对象的类tmixFilterResult。这个类扩展了multipleFilterResult类flowCore包和flowClust类。操作定义，像multipleFilterResult，%in%和Subset，也可以split类tmixFilterResult类。同样，也可以应用于设计检索过滤（聚类）信息从一个flowClust对象的方法或功能tmixFilterResult对象。这些措施包括criterion，ruleOutliers，ruleOutliers<-，Map，posterior，importance，uncertainty和getEstimates。也可绘制的过滤结果的各种功能（见下面的链接）。
If filter@K has a length >1, the function returns an object of class tmixFilterResultList. This class extends both the flowClustList class and the multipleFilterResult class. Note that when a tmixFilterResultList object is used in place of a tmixFilterResult object, in most cases the list element corresponding to the best model will be extracted and passed
如果filter@K有一个长度大于1，函数返回一个对象的类tmixFilterResultList。这个类扩展flowClustList类multipleFilterResult类。请注意，当tmixFilterResultList对象在tmixFilterResult对象的地方使用，在大多数情况下，列表元素对应的最佳模式将被提取并通过
作者（S）----------Author(s)----------
Raphael Gottardo <<a href="mailto:raph@stat.ubc.ca">raph@stat.ubc.ca</a>>, Kenneth Lo <<a href="mailto:c.lo@stat.ubc.ca">c.lo@stat.ubc.ca</a>>
参考文献----------References----------
参见----------See Also----------
flowClust, summary, plot, density, hist, Subset, split, ruleOutliers, Map
flowClust，summary，plot，density，hist，Subset，split，ruleOutliers，Map
举例----------Examples----------
### The example below largely resembles the one in the flowClust[＃＃下面的例子在很大程度上类似于一个在flowClust]
### man page. The main purpose here is to demonstrate how the[＃man页。这里的主要目的是为了演示如何]
### entire cluster analysis can be done in a fashion highly[＃整个聚类分析，可以做一个时尚的高度]
### integrated into flowCore.[＃集成成flowCore。]
data(rituximab)
### create a filter object[＃创建一个过滤器对象]
s1filter <- tmixFilter("s1", c("FSC.H", "SSC.H"), K=1)
### cluster the data using FSC.H and SSC.H[＃聚类的数据使用FSC.H和SSC.H]
res1 <- filter(rituximab, s1filter)
### remove outliers before proceeding to the second stage[＃删除，然后再进行第二阶段的离群]
# %in% operator returns a logical vector indicating whether each[％％操作符返回一个逻辑向量指示是否每个]
# of the observations lies inside the gate or not[观测在于内部的门或不]
rituximab2 <- rituximab[rituximab %in% res1,]
# a shorthand for the above line[上述线路的简写]
rituximab2 <- rituximab[res1,]
# this can also be done using the Subset method[这也可以使用子集方法]
rituximab2 <- Subset(rituximab, res1)
### cluster the data using FL1.H and FL3.H (with 3 clusters)[＃使用FL1.H和FL3.H（3聚类与聚类的数据）]
s2filter <- tmixFilter("s2", c("FL1.H", "FL3.H"), K=3)
res2 <- filter(rituximab2, s2filter)
show(s2filter)
show(res2)
summary(res2)
# to demonstrate the use of the split method[证明使用分割法]
split(rituximab2, res2)
split(rituximab2, res2, population=list(sc1=c(1,2), sc2=3))
# to show the cluster assignment of observations[显示聚类分配的意见]
table(Map(res2))
# to show the cluster centres (i.e., the mean parameter estimates[显示聚类中心（即平均参数估计]
# transformed back to the original scale) and proportions[转换回原来的规模）和比例]
getEstimates(res2)
### demonstrate the use of various plotting methods[＃展示使用各种绘图方法]
# a scatterplot[散点图]
plot(rituximab2, res2, level=0.8)
plot(rituximab2, res2, level=0.8, include=c(1,2), grayscale=TRUE,
pch.outliers=2)
# a contour / image plot[轮廓/图像图]
res2.den <- density(res2, data=rituximab2)
plot(res2.den)
plot(res2.den, scale="sqrt", drawlabels=FALSE)
plot(res2.den, type="image", nlevels=100)
plot(density(res2, include=c(1,2), from=c(0,0), to=c(400,600)))
# a histogram (1-D density) plot[直方图（一维密度）图]
plot(rituximab2, res2, "FL1.H")
### to demonstrate the use of the ruleOutliers method[＃展示的使用的ruleOutliers方法]
summary(res2)
# change the rule to call outliers[改变规则调用离群]
ruleOutliers(res2) <- list(level=0.95)
# augmented cluster boundaries lead to fewer outliers[增强聚类的边界导致更少的离群]
summary(res2)
# the following line illustrates how to select a subset of data [下面一行演示了如何选择一个数据子集]
# to perform cluster analysis through the min and max arguments;[min和max参数来执行，通过聚类分析;]
# also note the use of level to specify a rule to call outliers[还注意到使用指定的规则来调用离群水平]
# other than the default[比默认]
s2t <- tmixFilter("s2t", c("FL1.H", "FL3.H"), K=3, B=100,
min=c(0,0), max=c(400,800), level=0.95, z.cutoff=0.5)
filter(rituximab2, s2t)
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 17:39:34
