normalizeWithinArrays(limma)
normalizeWithinArrays()所属R语言包:limma
Normalize Within Arrays
标准化数组中
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Normalize the expression log-ratios for one or more two-colour spotted microarray experiments so that the log-ratios average to zero within each array or sub-array.
数比率为一个或多个两色的斑点芯片实验标准化表达log比率平均每个阵列或子阵内为零。
用法----------Usage----------
normalizeWithinArrays(object, layout, method="printtiploess", weights=object$weights, span=0.3, iterations=4, controlspots=NULL, df=5, robust="M", bc.method="subtract", offset=0)
MA.RG(object, bc.method="subtract", offset=0)
RG.MA(object)
参数----------Arguments----------
参数:object
object of class list, RGList or MAList containing red and green intensities constituting two-color microarray data.
类对象list,RGList或MAList含有红色和绿色的强度,构成两色的微阵列数据。
参数:layout
list specifying the dimensions of the spot matrix and the grid matrix. For details see PrintLayout-class.
列出指定的点矩阵和网格矩阵的尺寸。有关详情,请参阅PrintLayout-class。
参数:method
character string specifying the normalization method. Choices are "none", "median", "loess", "printtiploess", "composite", "control" and "robustspline". A partial string sufficient to uniquely identify the choice is permitted.
字符串指定的规范化方法。选择是"none""median","loess","printtiploess","composite","control"和"robustspline"。部分字符串足以唯一标识的选择是允许的。
参数:weights
numeric matrix or vector of the same size and shape as the components of object containing spot quality weights.
数字矩阵或向量object含现场质量权重的组件相同的大小和形状。
参数:span
numeric scalar giving the smoothing parameter for the loess fit
loess适合平滑参数的数字标
参数:iterations
number of iterations used in loess fitting. More iterations give a more robust fit.
黄土装修中使用的迭代数。更多的迭代给出了更强大的契合。
参数:controlspots
numeric or logical vector specifying the subset of spots which are non-differentially-expressed control spots, for use with method="composite" or method="control".
数字或逻辑向量指定的非差异表达的控制点的点集,使用method="composite"或method="control"。
参数:df
degrees of freedom for spline if method="robustspline".
样条如果method="robustspline"自由度。
参数:robust
robust regression method if method="robustspline". Choices are "M" or "MM".
如果method="robustspline"稳健回归方法。选择是"M"或"MM"。
参数:bc.method
character string specifying background correct method, see backgroundCorrect for options.
字符串指定背景正确的方法,请参阅backgroundCorrect选项。
参数:offset
numeric value, intensity offset used when computing log-ratios, see backgroundCorrect.
数值,强度抵消使用log的比率计算时,看到backgroundCorrect。
Details
详情----------Details----------
Normalization is intended to remove from the expression measures any systematic trends which arise from the microarray technology rather than from differences between the probes or between the target RNA samples hybridized to the arrays.
标准化的目的是从表达中删除的任何措施,从芯片技术,而不是从之间的探针杂交阵列的靶RNA样品之间的差异或出现系统性的趋势。
This function normalizes M-values (log-ratios) for dye-bias within each array. Apart from method="none" and method="median", all the normalization methods make use of the relationship between dye-bias and intensity. Method "none" computes M-values and A-values but does no normalization. Method "median" subtracts the weighted median from the M-values for each array.
此功能恢复正常,每个阵列内的染料偏见的M-值(log比率)。除了method="none"和method="median",所有的规范化方法使染料偏见和强度之间的关系。方法"none"计算的M-值和A值,但不会标准化。方法"median"减去从每个阵列的m值的加权中位数。
The loess normalization methods ("loess", "printtiploess" and "composite") were proposed by Yang et al (2001, 2002). Smyth and Speed (2003) review these methods and describe how the methods are implemented in the limma package, including choices of tuning parameters. More information on the loess control parameters span and iterations can be found under loessFit. The default values used here are equivalent to those for the older function stat.ma in the sma package.
黄土标准化的方法("loess","printtiploess"和"composite")由杨等人(2001年,2002年)的建议。史密斯和速度(2003)检讨这些方法,并介绍了如何实现的方法是在limma包,其中包括调整参数的选择。黄土控制参数的更多信息span和iterations可以下loessFit。这里使用默认值,相当于旧功能的stat.ma SMA封装。
Oshlack et al (2004) consider the special issues that arise when a large proportion of probes are differentially expressed. They propose an improved version of composite loess normalization, which is implemented in the "control" method. This fits a global loess curve through a set of control spots, such as a whole-library titration series, and applies that curve to all the other spots.
oshlack等(2004)认为,出现大比例的探针时差异表达的特殊问题。他们提出了一个复合黄土标准化,这是在"control"方法来实现的改进版本。这符合全球通过一组控制点,如整个图书馆滴定系列,黄土曲线,该曲线适用于所有的其他景点。
The "robustspline" method calls normalizeRobustSpline. See that function for more documentation.
"robustspline"方法调用normalizeRobustSpline。看到更多的文档的功能。
MA.RG converts an unlogged RGList object into an MAList object. MA.RG(object) is equivalent to normalizeWithinArrays(object,method="none").
MA.RG转换未记录的RGListMAList对象的对象。 MA.RG(object)相当于normalizeWithinArrays(object,method="none")的。
RG.MA(object) converts back from an MAList object to a RGList object with unlogged intensities.
RG.MA(object)MAList对象转换回RGList对象未记录的强度。
weights is normally a matrix giving a quality weight for every spot on every array. If weights is instead a vector or a matrix with only one column, then the weights will be assumed to be the same for every array, i.e., the weights will be probe-specific rather than spot-specific.
weights通常是给每个阵列上的每个点的质量,重量矩阵。 weights如果而是只有一个列向量或矩阵,那么权重将被认为是相同的,即每个阵列,重量将是具体的,而不是具体点探针。
值----------Value----------
An object of class MAList. Any components found in object will preserved except for R, G, Rb, Gb and other.
对象类MAList。在object发现任何组件将保留R,G,Rb,Gb和other除外。
作者(S)----------Author(s)----------
Gordon Smyth
参考文献----------References----------
参见----------See Also----------
An overview of limma functions for normalization is given in 05.Normalization. In particular, see normalizeBetweenArrays for between-array normalization.
在05.Normalization标准化limma功能概述。尤其是看到normalizeBetweenArrays阵列之间的标准化。
The original loess normalization function was the statma funtion in the sma package. normalizeWithinArrays is a direct generalization of that function, with more options and with support for quantitative spot quality weights.
原黄土标准化功能statmafuntion SMA封装。 normalizeWithinArrays是该函数的直接概括,更多的选择和支持定量现场质量重量。
A different implementation of loess normalization methods, with potentially different behavior, is provided by the maNorm in the marray package.
一个黄土标准化的方法不同的实施,可能不同的行为,提供了maNorm在marray包。
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。
|