normexp.fit.detection.p(limma)
normexp.fit.detection.p()所属R语言包：limma
Estimate Normexp Model Parameter Using Negative Controls Inferred from Regular Probes
估计Normexp模型参数使用从定期探针推断的阴性对照
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Detection p values from Illumina BeadChip microarray data can be used to infer negative control probe intensities from regular probe intensities by using detection p value information when negative control data are not available. The inferred negative control intensities can then be used in the background correction in the same way as those control data outputted from BeadChip used in the normexp.fit.control function.
可用于检测p从Illumina的BeadChip芯片数据的值，阴性对照的数据是不可用时，通过检测P值信息来推断阴性对照探针从常规的探针强度强度。推断阴性对照强度，然后可以以同样的方式使用背景校正，这些控制数据输出从BeadChipnormexp.fit.control功能。
用法----------Usage----------
normexp.fit.detection.p(x, detection.p="Detection")
参数----------Arguments----------
参数：x
object of class EListRaw-class or matrix containing raw intensities of regular probes for a series of microarrays
对象类EListRaw-class或matrix包含了一系列微阵列定期探针的原料强度
参数：detection.p
a character string giving the name of the component which contains detection p value information in x or a numeric matrix giving detection p values, Detection by default
一个字符串给组件的名称其中包含x或数字矩阵，检测p值，Detection的检测p值信息默认情况下，
Details
详情----------Details----------
This function estimates the normexp parameters in the same way as normexp.fit.control does, except that negative control probe intensities are inferred from regular probes by taking advantage of detection p value information rather than from the control probe profile outputted by BeadStudio.
这个功能估计在同样的方式为normexp.fit.control，除阴性对照探针强度推断定期探针通过检测P值信息的优势，从控制探针BeadStudio输出的配置文件，而不是normexp参数。
Calculation of detection p values in Illumina BeadChip data is based on the rank of probe intensities in the list of negative control probe intensities. Therefore, the detection p values can be used to find regular probes which have expression intensities falling into the range of negative control probe intensities. These probes give a good approximation to the real negative control data and thus can be used to estimate the mean and standard deviation of background intensities when negative control data is not available.
在Illumina的BeadChip数据检测p值的计算是基于探针强度阴性对照探针强度名单中的排名。因此，检测P值可用于定期探针落入阴性对照探针强度范围内的表达强度。这些探测器提供一个良好的近似真实的阴性对照数据，因此可以被用来估计背景强度的平均值和标准偏差时，阴性对照的数据是没有。
If x is an EListRaw-class object, this function will try to look for the component which includes detection p value matrix in x when detection.p is a character string. This function assumes that this component is located within the other component in x. The component name specified by detection.p should be exactly the same as the name of the detection p value component in x. If detection.p is a matrix, then this matrix will be used as the detection p value data used in this function.
x如果是EListRaw-class对象，这个函数会尝试看看的组件，其中包括检测在xp值矩阵时detection.p是一个字符串。这个函数假设在位于otherx组件，这个组件。 detection.p指定组件的名称应该是完全相同的检测p的x值组件的名称相同。如果detection.p是一个矩阵，这个矩阵将被用来作为检测p值在这个函数中使用的数据。
If x is an matrix object, then detection.p has to be a data matrix which includes detection p values.
x如果是matrix对象，然后detection.p是一个数据矩阵，其中包括检测p值。
When detection.p is a matrix, it has to have the same dimension as that of x.
当detection.p是matrix，它必须具有相同尺寸的x。
This function will replace the detection p values with 1 subtracted by these values if high intensity probes have detection p values less than those from low intensity probes.
此功能将取代这些值中减去1的检测带够值，如果有高强度探针检测p值比那些从低强度探针。
Note that when control data are available, the normexp.fit.control function should be used instead.
请注意，控制数据可用时，normexp.fit.control函数应该被用来代替。
值----------Value----------
A matrix containing estimated parameters with rows being arrays and with columns being parameters. Column names are mu, logsigma and logalpha.
矩阵参数估计是阵列的行和列参数。列名mulogsigma和logalpha。
作者（S）----------Author(s)----------
Wei Shi and Gordon Smyth
参考文献----------References----------
参见----------See Also----------
nec calls this function to get the parameters of the normal+exponential convolution model when control probe profile file is not available and then calls normexp.signal to perform the background correction.
nec调用这个函数来获得正常+指数的褶积模型的参数控制探针配置文件，然后调用normexp.signal进行背景校正。
normexp.fit.control estimates normexp parameters using control data outputted by BeadStudio.
normexp.fit.control估计normexp参数使用由BeadStudio输出的控制数据。
normexp.fit estimates normexp parameters using a saddle-point approximation or other mothods.
normexp.fit估计使用的鞍点逼近或其他mothods normexp参数。
An overview of background correction functions is given in 04.Background.
背景校正功能概述04.Background的。
举例----------Examples----------
## Not run: [＃无法运行：]
# read in BeadChip data which do not have control data available[BeadChip数据，而不必控制数据读取]
x <- read.ilmn(files="sample probe profile")
# estimated normexp parameters[估计normexp参数]
normexp.fit.detection.p(x)
# normalization using inferred negative controls[标准化的使用推断负对照]
y <- neqc(x)
## End(Not run)[＃结束（不运行）]
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 23:21:09
