fitWithin(stepNorm)
fitWithin()所属R语言包:stepNorm
Simple location normalization function for cDNA microarray data
cDNA微阵列数据的标准化功能简单的位置
译者:生物统计家园网 机器人LoveR
描述----------Description----------
This function performs location normalization on cDNA micoroarray. It operates on class marrayRaw or class marrayNorm. It allows the user to choose from a set of three basic normalization procedures.
本功能对基因micoroarray执行位置标准化。它的运作类marrayRaw类marrayNorm。它允许用户从一组三个基本标准化程序选择。
用法----------Usage----------
fitWithin(x.fun = "maA", y.fun = "maM", z.fun = TRUE, subset=TRUE, fun = "medfit", ...)
参数----------Arguments----------
参数:x.fun
Name of accessor method for spot intensity, usually maA.
点的强度,通常maA存取方法的名称。
参数:y.fun
Name of accessor method for spot statistics, usually the log-ratio maM.
现货统计的存取方法,通常数比maM的名称。
参数:z.fun
Name of accessor method for spot statistic used to stratify the data, usually a layout parameter, e.g. maPrintTip or maCompPlate. If z is not a character, e.g. NULL, the data are not stratified.
存取点统计方法采用分层的数据,通常是一个布局参数的名称,如maPrintTip或maCompPlate。 z如果是不是一个字符,例如NULL,该数据是不分层。
参数:subset
A "logical" or "numeric" vector indicating the subset of points used to compute the normalization values.
“逻辑”或“数字”向量表示用来计算标准化值点的子集。
参数:fun
Character string specifying the normalization procedure:
字符串指定标准化过程:
medfitfor global median location normalization
medfitfor全球中位数位置标准化
rlmfitfor global intensity or A-dependent location normalization using the rlm function
全球rlmfitfor强度或依赖一个位置标准化使用rlm函数
loessfitfor global intensity or A-dependent location normalization using the loess function
全球loessfitfor强度或依赖一个位置标准化使用loess函数
参数:...
Miscs arguments to be passed in fun
miscsfun要传递的参数
Details
详情----------Details----------
Normalization is typically performed on the expression ratios of cDNA microarray data, using the function specified by argument fun. Currently, this function is to be chosen from: medfit (median), rlmfit (rlm) and loessfit(loess). When z.fun is provided as a character string, for example, maPrintTip, the normalization procedure is operated within each print-tip of the slide.
标准化通常进行cDNA微阵列数据的表达率,使用参数fun指定的函数。目前,这个功能是选择:medfit(中位数),rlmfit(RLM)和loessfit(黄土)。当z.fun作为字符串,例如,maPrintTip,规范化的程序运行在每个幻灯片的打印头。
值----------Value----------
The function fitWithin returns a function(F) with bindings for x.fun, y.fun, z.fun, subset and fun. When the function F is evaluated with an object of class marrayNorm or marrayRaw, it carries out normalization and returns an object of class marrayFit that contains the normalization information as a list with the following list components:
功能fitWithin返回F,x.fun,y.fun,z.fun和subset绑定函数(fun)。当函数F类对象被评为marrayNorm或marrayRaw,开展标准化,并返回一个类的对象marrayFit包含列表标准化,信息下面的列表组件:
参数:varfun
: A character vector of names of predictor variables.
:特征向量的预测变量的名称。
参数:x
: A numeric matrix of predictor variables.
:预测变量的数字矩阵。
参数:y
: A numeric matrix of repsonses.
:repsonses数字矩阵。
参数:residuals
: A numeric matrix of normalized values (typically log ratios (M)).
数字矩阵的标准化值(通常log比率(M))。
参数:fitted
: A numeric matrix of the fitted values.
:拟合值的数字矩阵。
参数:enp
: The equivalent number of parameters; see loess.
:等效参数的数目;看到loess
参数:df.residual
: The residual degrees of freedom.
:自由的残留度。
参数:fun
: A character string indicating the name of the function used for normalization.
:一个字符串,指示标准化的函数的名称。
Note that the residuals component stores the normalized ratios.
注意residuals组件存储归一的比率。
作者(S)----------Author(s)----------
Yuanyuan Xiao, <a href="mailto:yxiao@itsa.ucsf.edu">yxiao@itsa.ucsf.edu</a>, <br>
Jean Yee Hwa Yang, <a href="mailto:jean@biostat.ucsf.edu">jean@biostat.ucsf.edu</a>
参考文献----------References----------
for cDNA microarray data. In M. L. Bittner, Y. Chen, A. N. Dorsel, and E. R. Dougherty (eds), Microarrays: Optical Technologies and Informatics, Vol. 4266 of Proceedings of SPIE.
参见----------See Also----------
fit2DWithin
fit2DWithin
举例----------Examples----------
## using the swirl data as example[#使用为例漩涡数据]
data(swirl)
## median normalization[#中位数标准化]
med <- fitWithin(fun="medfit")
swirl1.med <- med(swirl[,1])
norm.M <- swirl1.med$residuals ## matrix of normalized ratios[#标准化比率的矩阵]
## rlm normalization[#RLM标准化]
rlmF <- fitWithin(fun="rlmfit")
swirl1.rlm <- rlmF(swirl[,1])
## loess normalization, default span=0.4[#黄土标准化,默认跨度= 0.4]
loessF <- fitWithin(fun="loessfit")
swirl1.loess <- loessF(swirl[,1])
## loess normalization, span=0.2[#黄土标准化,跨度= 0.2]
loessF.1 <- fitWithin(fun="loessfit", span=0.2)
swirl1.loess.1 <- loessF.1(swirl[,1])
## within-printtip loess normalization[#内printtip黄土标准化]
loessP <- fitWithin(z.fun="maPrintTip", fun="loessfit")
swirl1.loessP <- loessP(swirl[,1])
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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