lvs(LVSmiRNA)
lvs()所属R语言包：LVSmiRNA
Least Variant Set selection and Normalization Function(s)
至少变异集选择和规范化功能（S）
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Selects the Least Variant Set of mircoRNAs, according to the chosen proportion of miRNAs expected not to vary between arrays. Then performs normalization.
选择最mircoRNAs变种集，按比例预计不会改变阵列之间的miRNA的选择。然后执行标准化。
用法----------Usage----------
lvs(RG,RA,ref,proportion=0.7,df=3,method=c("joint","rlm"),
cov.formula=c("weighted","asymptotic"),
spar=NULL,normalize.method=c("vsn","smooth.spline","mixed"),
summarize.args=NULL,stratify=TRUE,n.strata=3,
level=c("mir","probe"),Atransf=c("sqrt","log"),keep.iset=FALSE,clName,
verbose=FALSE,...)
## S3 method for class 'RGList'
lvs(RG,RA,ref,proportion=0.7,df=3,method=c("joint","rlm"),
cov.formula=c("weighted","asymptotic"),
spar=NULL,normalize.method=c("vsn","smooth.spline","mixed"),
summarize.args=NULL,stratify=TRUE,n.strata=3,
level=c("mir","probe"),Atransf=c("sqrt","log"),
keep.iset=FALSE,clName,verbose=FALSE,...)
## S3 method for class 'EList'
lvs(RG,RA,ref,proportion=0.7,df=3,method=c("joint","rlm"),
cov.formula=c("weighted","asymptotic"),
spar=NULL,normalize.method=c("vsn","smooth.spline","mixed"),
summarize.args=NULL,stratify=TRUE,n.strata=3,
level=c("mir","probe"),Atransf=c("sqrt","log"),keep.iset=FALSE,clName,
verbose=FALSE,...)
参数----------Arguments----------
参数：RG
an object of class EList or RGList
对象类EList或RGList
参数：RA
a list contaning components residual standard deviations, chi-square statistics and array effects. It can be computed by estVC. If not provided it will computed (slower),
列表contaning组件剩余标准差，卡方统计和阵列效果。它可以计算estVC。如果没有提供，它会计算（慢），
参数：proportion
the proportion below which miRNAs are expected not to vary between arrays. Default is set to 0.7.
miRNA的比例低于预期不改变阵列之间。默认设置为0.7。
参数：ref
reference array to be used for normalization. Default is set to mean of array effects across samples.
参考阵列可用于标准化。默认设置是指阵列跨样本的影响。
参数：df
the desired equivalent number of degrees of freedom(trace of the smooth matrix) in smoothing spline.
所需的同等数量的自由度（顺利矩阵的迹线），在光滑样条。
参数：method
character string specifying the estimating algorithm to be used. Choices are "joint" and "rlm".
字符串指定要使用的估计算法。选择“联合”，“RLM”。
参数：cov.formula
character string specifying the covariance formula to be used. Choices are "weighted" and "asymptotic".
字符串指定要使用的协方差公式。 “加权”和“渐进”的选择。
参数：spar
smoothing parameter, typicallly in (0,1].
平滑参数，typicallly在（0,1]。
参数：normalize.method
character string specifying the normalization method to be used. Choices are "smooth.spline" and "vsn".
字符串指定要使用的规范化方法。选择是的“smooth.spline”和“VSN”。
参数：summarize.args
a named list containnig components from argument of summarize.
一个名为列表containnig元件参数summarize。
参数：stratify
logical, if TRUE selection of least variant set will be stratified by expression level.
逻辑，如果真选择至少变异集的分层表达水平。
参数：n.strata
integer giving the number of strata.
整数，地层的数量。
参数：level
character string specifying the normalization performed at miRNA level or probe-level.
miRNA的水平或探针级执行字符串指定的标准化。
参数：Atransf
Which transformation to use for Array Effect
改造使用阵列的影响
参数：keep.iset
return the LVS ids
返回LVS的IDS
参数：clName
Cluster object. See estVC.
聚类对象。看到estVC。
参数：verbose
Verbose computation
详细计算
参数：...
...
...
Details
详情----------Details----------
lvs works by first identifying least variant set (LVS) with the smallest array-to-array variation. The total information extracted from probe-level intensity data of all samples is modeled as a function of array and probe effect in order to select the reference set for normalization. If the residual variances and array effects are available, lvs runs faster because the step of robust linear modeling has already been done.
lvs的工作原理是先确定最小的阵列到阵列的变化，至少的变种集（LVS）的。从所有样本的探针强度数据中提取的总信息是仿照阵列和探测效果的功能，以便选择参考集的标准化。如果剩余的差异和阵列效果，lvs运行速度更快，因为强大的线性建模的步骤已经完成。
Once the LVS miRNAs are identified, the normalization is performed using VSN or smooth.spline.
一旦LVS miRNA的鉴定，使用VSN或smooth.spline标准化。
值----------Value----------
An object of the same class as RG.
作为RG同一类的对象。
参数：G
matrix containing the normalized intensities for each array with miRNAs as rows and arrays as columns.
矩阵含有作为miRNA的行和列的阵列，每个阵列归强度。
参数：Gb
matrix containing the background intensities for each array with probes as rows and arrays as columns.
矩阵包含行和列的阵列探针为每个阵列的背景强度。
参数：targets
data frame with column FileName giving the names of the files read, with column Sample giving the names of the samplse.
数据柱框架FileName给的文件名读取列，Sample的的samplse给予的名称。
参数：genes
data frame containing annotation information about the probes, for examples miRNA names and IDs and positions on the array.
数据框的例子包含有关探针的注释信息，miRNA的阵列上的名称和ID和位置。
参数：source
character string giving the image analysis program name.
给图像分析程序名称的字符串。
参数：preprocessing
list with components Background, Normalization, is.log, Summarization indicate which pre-processing step has been done.
与组件列表Background，Normalization，is.log，Summarization前处理步骤已经完成。
作者（S）----------Author(s)----------
Stefano Calza <stefano.calza@biostatistics.it>, Suo Chen and Yudi Pawitan.
参考文献----------References----------
<h3>See Also</h3>
举例----------Examples----------
## Not run: [＃无法运行：]
# Starting from an Elist object called MIR[从所谓的miR Elist对象]
data("MIR-spike-in")
AA <- estVC(MIR,method="joint")
bb <- lvs(MIR,RA=AA,level="probe")
##It can also run with object RA missing, but taking longer time[＃它也可以运行与类风湿性关节炎失踪对象，但以较长的时间]
cc <- lvs(MIR)
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 23:53:04
