gaussNorm(flowStats)
gaussNorm()所属R语言包：flowStats
Per-channel normalization based on landmark registration
每通道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 funciton normalizes a set of flow cytometry data samples by identifying and aligning the high density regions (landmarks or peaks) for each channel. The data of each channel is shifted in such a way that the identified high density regions are moved to fixed locations called base landmarks.
此功能可按标准化，通过确定和调整每个通道的高密度区域（地标或峰）流式单元仪数据样本集。每个通道的数据转移在这种方式确定的高密度区域转移到固定地点称为碱基标。
用法----------Usage----------
gaussNorm (flowset, channel.names, max.lms=2, base.lms=NULL,
peak.density.thr=0.05, peak.distance.thr=0.05, debug=FALSE, fname='')
参数----------Arguments----------
参数：flowset
A flowSet.
AflowSet。
参数：channel.names
A character vector of flow parameters in flowset to be normalized.
一个flowset流参数的特征向量被归。
参数：max.lms
A numeric vector of the maximum number of base landmarks to be used for normalizing each channel. If it has only one value that will be used as the maximum number of base landmarks for all the channels.
碱基标志性建筑的最大数量的数字向量，以用于每个通道的标准化。如果只有一个值将作为碱基标志性建筑的所有通道的最大数量。
参数：base.lms
A list of vector for each channel that contains the base landmarks for normalizing that channel. If not specified the base landmarks are computed from the set of extracted landmarks.
每个通道包含标准化该通道的碱标列表的一个向量。如果没有指定碱基的地标计算提取的地标集。
参数：peak.density.thr
The peaks with density value less than "peak.density.thr times maximum peak density" are discarded.
与密度值比“peak.density.thr倍的最大峰值电流密度”少峰被丢弃。
参数：peak.distance.thr
The sequences of peaks that are located closer than "peak.distance.thr times range of data" are identified. Then for each sequence only one peak (the one with the highest intensity value) is used as a landmark. In other words no two landmarks are located closer than "peak.distance.thr times range of data" to each other.
位于接近“peak.distance.thr倍范围内的数据”确定峰的序列。然后为每个序列只有一个峰值（强度值最高的国家之一）被用来作为一个具有里程碑意义。换句话说，没有两个标志性建筑是位于比“peak.distance.thr倍的数据范围”彼此接近。
参数：debug
Logical. Forces the function to draw before and after normalization plots for each sample. The plot of the i-th sample is stored in paste(fname, i) file.
逻辑。强制功能之前和之后，每个样品的标准化图绘制。 paste(fname, i)文件中存储的第i个样本的图。
参数：fname
The pre- and post- normalization plots of the i-th sample is stored in paste(fname, i) file if debug is set to TRUE. If default value is used the plots are drawn on separate X11 windows for each sample. In this case, the function waits for a user input to draw the plots for the next sample.
图预标准化后的第i个样本被储存在paste(fname, i)文件，如果调试设置TRUE。如果使用默认值图绘制每个样品单独的X11窗口。在这种情况下，功能等待用户输入，画下一个样品的图。
Details
详情----------Details----------
Normalization is archived in three phases: (i) identifying high-density regions (landmarks) for each flowFrame in the flowSet for a single channel; (ii) computing the best matching between the landmarks and a set of fixed reference landmarks for each channel called base landmarks; (iii) manipulating the data of each channel in such a way that each landmark is moved to its matching base landmark. Please note that this normalization is on a channel-by-channel basis. Multiple channels are normalized in a loop.
标准化存档，在三个阶段：（一）确定每个单一通道的flowFrameflowSet高密度区域（地标），（二）计算之间的地标和一套最佳匹配每个通道称为碱基标固定的参考地标;（三）操纵在这样一个具有里程碑意义的，每个转移到与其匹配的基础上具有里程碑意义的方式每个通道的数据。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----------
A list with items flowset: normalized flowSet. confidence: a confidence measure of the normalization procedure.
与项目列表flowset归flowSet。 confidence：信任措施的标准化过程。
作者（S）----------Author(s)----------
Alireza Hadj Khodabakhshi
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$n2gate)
datr <- gaussNorm(dat, "CD8")$flowset
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。
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发表于 2012-2-25 18:09:41
