R语言 flowPlots包 StackedData-class()函数中文帮助文档(中英文对照)

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StackedData-class(flowPlots)
StackedData-class()所属R语言包：flowPlots

                                        Class "StackedData"
                                         类“StackedData”

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

Stacked data refers to gated data originating from an ICS Flow Cytometry experiment where the marker combinations for a subset of interest, say a given cell type, stimulus, and concentration, are "stacked".  A common type of marker is a cytokine.  A subset of stacked data could look like this:
堆积数据是指从ICS流式单元仪实验，在利益的一个子集的标记组合，说一个特定的单元类型，刺激，浓度的门数据，“堆叠”。常见的类型的标志，是一种单元因子。堆积数据的一个子集可能看起来像这样：


Details

详情----------Details----------

The marker combinations in the stacked data should be ordered within each subset of  interest (for example: subjectID, celltype, concentration, and stimulation) to match the marker matrix.  If the data are not in this order, it should be sorted into this order before using the computeProfileData, computeMarginalData, computePFDData,  computePFDPartsData methods.  The computeMarkers method can be used to compute the marker matrix used by these methods.  If the matrix computed does not match the order of your data, then you can supply your own marker matrix, assign it to the marker data slot of a StackedData object, and then use the 'compute' methods to compute the other types of data.
在堆叠的数据标记的组合，应责令内每一个感兴趣的子集（例如：subjectID，celltype，浓度，并刺激）相匹配的标记矩阵。如果数据是不是这个顺序，应该把这个顺序排序使用前computeProfileData，computeMarginalData，computePFDData，computePFDPartsData方法。 computeMarkers方法可以用来计算这些方法所使用的标记矩阵。矩阵计算，如果不匹配，为了您的数据，那么你可以提供自己的标记矩阵，它分配给标记的数据插槽一个StackedData对象，然后使用“计算”的方法来计算其他类型的数据。


类的对象----------Objects from the Class----------

Objects can be created by calls of the form:
创建对象可以通过检测的形式：

stackedDataObject = new("StackedData", stackedData=NA, profileData=NA, marginalData=NA, pfdData=NA, pfdPartsData=NA, markers=NA )
stackedDataObject = new("StackedData", stackedData=NA, profileData=NA, marginalData=NA, pfdData=NA, pfdPartsData=NA, markers=NA )


插槽----------Slots----------




stackedData: "data.frame" of stacked data
stackedData："data.frame"叠数据




profileData: "data.frame" of profile data
profileData："data.frame"个人资料数据




marginalData: "data.frame" of marginal data
marginalData："data.frame"边际数据




pfdData: "data.frame" of pfd data
pfdData："data.frame"PFD数据




pfdPartsData: "list" of "data.frame" 's of pfd parts data
pfdPartsData："list""data.frame"的PFD部分数据




markers: "matrix" of marker data
markers："matrix"标记数据


方法----------Methods----------




computeMarginalData signature(object = "StackedData", byVarNames = "character", idVarName = "character", percentVarName = "character", groupVarName = "character")
computeMarginalDatasignature(object = "StackedData", byVarNames = "character", idVarName = "character", percentVarName = "character", groupVarName = "character")




computeMarkers signature(markerNames = "character", includeAllNegativeRow = "logical")
computeMarkerssignature(markerNames = "character", includeAllNegativeRow = "logical")




computePFDData signature(object = "StackedData", byVarNames = "character", idVarName = "character", percentVarName = "character", groupVarName = "character")
computePFDDatasignature(object = "StackedData", byVarNames = "character", idVarName = "character", percentVarName = "character", groupVarName = "character")




computePFDPartsData signature(object = "StackedData", byVarNames = "character", idVarName = "character", percentVarName = "character", groupVarName = "character")
computePFDPartsDatasignature(object = "StackedData", byVarNames = "character", idVarName = "character", percentVarName = "character", groupVarName = "character")




computeProfileData signature(object = "StackedData", byVarNames = "character", idVarName = "character", percentVarName = "character", groupVarName = "character")
computeProfileDatasignature(object = "StackedData", byVarNames = "character", idVarName = "character", percentVarName = "character", groupVarName = "character")

# getters
＃干将




marginalData signature(object = "StackedData")
marginalDatasignature(object = "StackedData")




markers signature(object = "StackedData")
标记signature(object = "StackedData")




pfdData signature(object = "StackedData")
pfdDatasignature(object = "StackedData")




pfdPartsData signature(object = "StackedData")
pfdPartsDatasignature(object = "StackedData")




profileData signature(object = "StackedData")
profileDatasignature(object = "StackedData")




stackedData signature(object = "StackedData")
stackedDatasignature(object = "StackedData")

# setters
＃setter方法




marginalData signature(object = "StackedData", value = "data.frame")
marginalDatasignature(object = "StackedData", value = "data.frame")




markers signature(object = "StackedData", value = "matrix")
标记signature(object = "StackedData", value = "matrix")




pfdData signature(object = "StackedData", value = "data.frame")
pfdDatasignature(object = "StackedData", value = "data.frame")




pfdPartsData signature(object = "StackedData", value = "list")
pfdPartsDatasignature(object = "StackedData", value = "list")




profileData signature(object = "StackedData", value = "data.frame")
profileDatasignature(object = "StackedData", value = "data.frame")




stackedData signature(object = "StackedData", value = "data.frame")
stackedDatasignature(object = "StackedData", value = "data.frame")


作者（S）----------Author(s)----------


N. Hawkins, Fred Hutchinson Cancer Research Center, Seattle, WA



参见----------See Also----------

markers, profileData, marginalData, pfdData,
markers，profileData，marginalData，pfdData


举例----------Examples----------


# View the Data Slots in StackedData[查看在StackedData的“数据插槽]
showClass("StackedData")

# Load stacked data[载入堆叠数据]
data(adultsNeonates)
# Create a stacked data object[创建一个堆叠的数据对象]
stackedDataObject = new("StackedData", stackedData=adultsNeonates)

# Compute the marker data and set the marker data slot[计算标记的数据和设置标记的数据槽]
# The marker matrix computed here matches the order of the marker combinations[这里的标记矩阵计算匹配的标记组合的顺序]
# in the adultsNeonates stacked data within each subset of interest[堆放在adultsNeonates利益的每个子集内的数据]
markerNames = c("TNFa","IL6","IL12","IFNa")
markers = computeMarkers(markerNames,includeAllNegativeRow=TRUE)
markers(stackedDataObject) = markers

# Compute the profile data and set the profile data slot[计算个人资料数据，并设置文件数据槽]
byVarNames = c("stim", "concGroup", "cell")
profileData = computeProfileData(stackedDataObject, byVarNames, "id", "percentAll", "group")
profileData(stackedDataObject) = profileData

# Compute the marginal data and set the marginal data slot[计算边际的数据和设置边缘的数据槽]
byVarNames = c("stim", "concGroup", "cell")
marginalData = computeMarginalData(stackedDataObject, byVarNames, "id", "percentAll", "group")
marginalData(stackedDataObject) = marginalData

# Compute the pfd data and set the pfd data slot[计算PFD的数据和设置PFD数据槽]
byVarNames = c("stim", "concGroup", "cell")  
pfdData = computePFDData(stackedDataObject, byVarNames, "id", "percentAll", "group")
pfdData(stackedDataObject) = pfdData

# Compute the pfd parts data and set the pfd parts data slot[PFD部分计算数据和设置PFD部分数据槽]
byVarNames = c("stim", "concGroup", "cell")
pfdPartsData = computePFDPartsData(stackedDataObject, byVarNames, "id", "percentAll", "group")
pfdPartsData(stackedDataObject) = pfdPartsData

# Get the data from the stacked data object[从堆放的数据对象获取数据]

markers = markers(stackedDataObject)
profileData = profileData(stackedDataObject)
marginalData = marginalData(stackedDataObject)
pfdData = pfdData(stackedDataObject)
pfdPartsData = pfdPartsData(stackedDataObject)


转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


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