warpSet(flowStats)
warpSet()所属R语言包：flowStats
Normalization based on landmark registration
标准化的基础上具有里程碑意义的登记
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function will perform a normalization of flow cytometry data based on warping functions computed on high-density region landmarks for individual flow channels.
此功能将根据个别流动渠道的高密度区域的地标计算的翘曲函数流式单元仪数据进行标准化。
用法----------Usage----------
warpSet(x, stains, grouping = NULL, monwrd = TRUE, subsample=NULL,
peakNr=NULL, clipRange=0.01, nbreaks=11, fres, bwFac=1.3,
warpFuns=FALSE, ...)
参数----------Arguments----------
参数：x
A flowSet.
AflowSet。
参数：stains
A character vector of flow parameters in x to be normalized.
一个x流参数的特征向量被归。
参数：grouping
A character indicating one of the phenotypic variables in the phenoData slot of x used as a grouping factor. The within-group and between-group variance is computed and a warning is issued in case the latter is bigger than the former, indicating the likely removal of signal by the normalization procedure.
字符显示phenoData插槽中的表型变量之一x作为分组因素。组内和组间方差的计算和发出警告的情况下，后者较前者更大，显示信号的标准化过程可能去除。
参数：monwrd
Logical. Compute strictly monotone warping functions. This gets directly passed on to landmarkreg.
逻辑。计算严格单调的变形功能。这个被直接传递给landmarkreg。
参数：subsample
Numeric. Reduce the number of events in each flowSet by sub sampling for all density estimation steps and the calculation of the warping functions. This can increase computation time for large data sets, however it might reduce the accuracy of the density estimates. To be used with care.
数字。所有密度估计的步骤和翘曲函数的计算子采样，减少事件的数量在每个flowSet通过。这可以增加计算时间，为大型数据集，但它可能会降低密度估计的准确性。要小心使用。
参数：peakNr
Numeric scalar. Force a fixed number of peaks to use for the normalization.
数字标。峰强制固定数量的使用标准化。
参数：clipRange
Only use peaks within a clipped data range. Essentially, the number indicates the percent of clipping on both sides of the data range, e.g. min(x) - 0.01 * diff(range(x)).
只用修剪的数据范围内的高峰。从本质上讲，数字表示的数据范围，双方的裁剪％，如min(x) - 0.01 * diff(range(x))。
参数：nbreaks
The number of spline sections used to approximate the data. Higher values produce more accurate results, however this comes with the cost of increaseqd computing times. For most data, the default setting is good enough.
使用近似数据的样条部分。较高的值产生更准确的结果，但是这种带有的increaseqd计算时间成本。对于大多数的数据，默认设置是不够好。
参数：fres
A named list of filterResultList objects. This can be used to speed up the process since the curv1Filter step can take quite some time.
filterResultList对象的命名列表。这可以用来加快进程以来，curv1Filter步骤可能需要相当长的一段时间。
参数：bwFac
Numeric of lenght 1 used to set the bandwidth factor by curv1Filter for smoothing of the density estimate.
数字长度1设置curv1Filter的平滑的密度估计的带宽因素。
参数：warpFuns
Logical indcating whether to return the normalized flowSet or a list of warping functions.
逻辑indcating是否返回归flowSet或翘曲功能列表。
参数：...
Further arguments that are passed on to landmarkreg.
进一步传递landmarkreg的论据。
Details
详情----------Details----------
Normalization is achived by first identifying high-density regions (landmarks) for each flowFrame in the flowSet for a single channel and subsequently by computing warping functions for each flowFrame that best align these landmarks. This is based on the algorithm implemented in the landmarkreg function in the fda package. An intermediate step classifies the high-density regions, see landmarkMatrix for details.
标准化achived首先确定每个的flowFrame在为一个单一的通道，每个flowSet最对齐这些地标，随后通过计算翘曲功能flowFrame高密度区域（地标）。这是基于该算法在landmarkregfda包的功能实现。一个中间步骤分为高密度区域，看到landmarkMatrix详情。
Please note that this normalization is on a channel-by-channel basis. Multiple channels are normalized in a loop.
请注意这是一个通道，通道的基础上的标准化。多渠道，归在一个循环。
值----------Value----------
The normalized flowSet if warpFuns is FALSE, otherwise a list of warping functions. Additional inforamtion is attached as the warping attribute to the flowSet in form of a list.
归flowSet如果warpFuns是FALSE，否则翘曲职能的名单。附加inforamtion是warping属性flowSet列表的形式。
注意----------Note----------
We currently use a patched fda version.
我们目前使用一个修补FDA版本。
作者（S）----------Author(s)----------
Florian Hahne
参考文献----------References----------
Springer 2002
参见----------See Also----------
curv1Filter, landmarkMatrix
curv1Filter，landmarkMatrix
举例----------Examples----------
data(ITN)
dat <- transform(ITN, "CD4"=asinh(CD4), "CD3"=asinh(CD3), "CD8"=asinh(CD8))
lg <- lymphGate(dat, channels=c("CD3", "SSC"),
preselection="CD4",scale=1.5)
dat <- Subset(dat, lg$n2gate)
datr <- warpSet(dat, "CD8", grouping="GroupID", monwrd=TRUE)
if(require(flowViz)){
d1 <- densityplot(~CD8, dat, main="original", filter=curv1Filter("CD8"))
d2 <- densityplot(~CD8, datr, main="normalized", filter=curv1Filter("CD8"))
plot(d1, split=c(1,1,2,1))
plot(d2, split=c(2,1,2,1), newpage=FALSE)
}
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。
|
发表于 2012-2-25 18:11:06
