normalizeVSN(limma)
normalizeVSN()所属R语言包:limma
Variance Stabilizing Normalization (vsn)
方差稳定标准化(VSN)
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Apply variance stabilizing normalization (vsn) to limma data objects.
方差稳定标准化(VSN)到limma的数据对象。
用法----------Usage----------
normalizeVSN(x, ...)
参数----------Arguments----------
参数:x
a numeric matrix, EListRaw or RGList object.
数字matrix,EListRaw或RGList对象。
参数:...
other arguments are passed to vsn
其他的参数被传递vsn
Details
详情----------Details----------
This is an interface to the vsnMatrix function from the vsn package. The input x should contain raw intensities. If x contains background and well as foreground intensities, these will be subtracted from the foreground intensities before vsnMatrix is called.
这是一个vsnMatrix从VSN包功能的接口。输入x应包含原始强度。如果x包含背景和前景强度,这些将被减去前vsnMatrix被称为前景强度。
Note that the vsn algorithm performs background correction and normalization simultaneously. If the data are from two-color microarrays, then the red and green intensities are treated as if they were single channel data, i.e., red and green channels from the same array are treated as unpaired. This algorithm is therefore separate from the backgroundCorrection, normalizeWithinArrays, then normalizeBetweenArrays paradigm used elsewhere in the limma package.
注意,VSN算法同时进行背景校正和规范化。如果数据从两色的芯片,然后在红色和绿色的强度视为他们的单通道数据,即从同一阵列,红色和绿色通道视为未成。因此,该算法是从独立的backgroundCorrection,normalizeWithinArrays,然后在别处使用在limma包normalizeBetweenArrays范式。
值----------Value----------
The class of the output depends on the input. If x is a matrix, then the result is a matrix of the same size. If x is an EListRaw object, then an EList object with expression values on the log2 scale is produced. For x is an RGList, then an MAList object with M and A-values on the log2 scale is produced.
取决于输入输出类。 x如果是一个矩阵,那么结果是一个同样大小的矩阵。 x如果是EListRaw对象,然后EList表达式的值对象的log2规模生产。 x是一个RGList,则MAListM和A值的log2规模的对象产生。
作者(S)----------Author(s)----------
Gordon Smyth
参考文献----------References----------
Variance stabilization applied to microarray data calibration and to the quantification of differential expression. Bioinformatics 18 Supplement 1, S96-S104.
参见----------See Also----------
An overview of LIMMA functions for normalization is given in 05.Normalization.
在05.Normalization标准化LIMMA功能概述。
See also vsn and vsnMatrix in the vsn package.
另见vsn和vsnMatrix在VSN包。
举例----------Examples----------
ngenes <- 100
narrays <- 4
x <- matrix(rnorm(ngenes*narrays),100,4)
y <- normalizeVSN(x)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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