flowType(flowType)
flowType()所属R语言包：flowType
flowType: Phenotyping Flow Cytometry Assays
flowType：表型流式单元仪检测
译者：生物统计家园网 机器人LoveR
描述----------Description----------
flowType uses a simple threshold, Kmeans, flowMeans or flowClust to partition every channel to a positive and a negative cell population. These partitions are then combined to generate a set of multi-dimensional phenotypes.
flowType使用一个简单的阈值，KMEANS，flowMeans或分区flowClust每到一个积极的和负面的单元群的通道。这些分区，然后结合产生了一套多维表型。
用法----------Usage----------
flowType(Frame, PropMarkers = NA, MFIMarkers = NA, Methods = "kmeans", MarkerNames="NULL")
参数----------Arguments----------
参数：Frame
A flowFrame (after transformation) that is going to be phenotyped.
（改造后）将被phenotyped的一个flowFrame。
参数：PropMarkers
A vector of the indexes or names of the markers for which cell proportions must be measured.
一个向量单元比例必须测量标志的名称或指标。
参数：MFIMarkers
A vector of the indexes or names of the markers for which MFIs must be measured.
为小额信贷机构必须测量标志的名称或指标向量。
参数：Methods
A vector of strings of length 1 or PropMarkers. Values can be "Kmeans", "flowMeans", "flowClust", or a numerical value. If only one method is provided the same method will be used for all of the channels.
一个字符串的长度为1或PropMarkers向量。值可以是KMEANS“，”flowMeans“，”flowClust“，或一个数值。如果只有一个方法是提供相同的方法将被用于所有的渠道。
参数：MarkerNames
A vector of names for the channels. If NULL, the names provided in Frame will be used.
频道名称的向量。如果NULL，Frame提供的名字将使用。
值----------Value----------
参数：<code>CellFreqs</code>:
Object of class "numeric" containing the cell frequencies measured for each phenotype. Phenotype names are assigned as labels.
Object类的"numeric"含有单元各型测量的频率。型名称作为标签分配。
参数：<code>MFIs</code>:
Object of class "matrix" containing the measured MFIs for each phenotype. Phenotype names are assigned as column labels and marker names as row labels.
Object类的"matrix"含有各型测量的小额信贷机构。型名称指定为列标签和行标签的标记名称。
参数：PropMarkers
A vector of the indexes or names of the markers for which cell proportions must be measured.
一个向量单元比例必须测量标志的名称或指标。
参数：MFIMarkers
A vector of the indexes or names of the markers for which MFIs must be measured.
为小额信贷机构必须测量标志的名称或指标向量。
参数：MarkerNames
A vector of names for the channels. If NULL, the names provided in Frame will be used.
频道名称的向量。如果NULL，Frame提供的名字将使用。
参数：Partitions
A matrix where each column shows the partitioning of the respective channel. 1 and 2 correspond to negative and positive, respectively.
一个矩阵，其中每列显示各通道的分区。 1和2对应的阴性和阳性，分别。
作者（S）----------Author(s)----------
Nima Aghaeepour
参考文献----------References----------
O'Neill, Tess M. Brodie, Habil Zare, John R. Mascola, Holger H. Hoos, Nelson Michael, Ryan R. Brinkman, and Mario Roederer. Early Immunologic Correlates of HIV Protection can be Identified from Computational Analysis of Complex Multivariate T-cell Flow Cytometry Assays. To be submitted to PLoS Computational Biology, 2011.
举例----------Examples----------
#Load the library[加载库]
library(flowType)
data(DLBCLExample)
MarkerNames <- c('Time', 'FSC-A','FSC-H','SSC-A','IgG','CD38','CD19','CD3','CD27','CD20', 'NA', 'NA')
#These markers will be analyzed[这些标记将分析]
PropMarkers <- 3:5
MFIMarkers <- PropMarkers
MarkerNames <- c('FS', 'SS','CD3','CD5','CD19')
#Run flowType[运行flowType]
Res <- flowType(DLBCLExample, PropMarkers, MFIMarkers, 'flowMeans', MarkerNames);
MFIs=Res@MFIs;
Proportions=Res@CellFreqs;
Proportions <- Proportions / max(Proportions)
#Select the 30 largest phenotypes[选择30个最大的表型]
index=order(Proportions,decreasing=TRUE)[1:30]
bp=barplot(Proportions[index], axes=FALSE, names.arg=FALSE)
text(bp+0.2, par("usr")[3]+0.02, srt = 90, adj = 0, labels = names(Proportions[index]), xpd = TRUE, cex=0.8)
axis(2);
axis(1, at=bp, labels=FALSE);
title(xlab='Phenotype Names', ylab='Cell Proportion')
#These phenotype can be analyzed using a predictive model (e.g., classification or regression)[这些表型可以使用预测模型（例如，分类或回归分析）]
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 18:12:12
