twoGaussiansNull(Ringo)
twoGaussiansNull()所属R语言包：Ringo
Estimate a threshold from Gaussian mixture distribution
估计高斯混合分布的阈值
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Function to estimate a threshold from Gaussian mixture distribution. The data is assumed to follow a mixture of two Gaussian distributions. The one Gaussian with the lower mean value is assumed to be the null distribution and probe levels are assigned p-values based on this null distribution. The threshold is then the minimal data value with an adjusted p-value smaller than a specified threshold.
从混合高斯分布函数来估计一个阈值。数据假设遵循两个高斯分布的混合物。较低的平均值，高斯被认为是空分布和探测水平分配基于此空分布的p值。阈值，然后最小数据值与调整后的p值小于指定的阈值。
用法----------Usage----------
twoGaussiansNull(x, p.adj.method = "BY", max.adj.p = 0.1, var.equal = FALSE, ...)
参数----------Arguments----------
参数：x
numeric vector of data values
数字数据值的向量
参数：p.adj.method
method for adjusting the p-values for multiple testing; must be one of p.adjust.methods
P-值调整为多个测试方法;必须是一个p.adjust.methods
参数：max.adj.p
which adjusted p-value to use as upper limit for estimating the threshold
调整p值上限使用估计的阈值
参数：var.equal
logical; is the variance of the two Gaussians assumed to be equal or different
逻辑;两个高斯方差假定为相同或不同
参数：...
further arguments passed on to function Mclust
通过进一步的论据运作Mclust
Details
详情----------Details----------
This function uses the package mclust to fit a mixture of two Gaussians to the data. The threshold is then estimated from the fitted Gaussian with the lower mean value.
使用此功能的包mclust的数据，以适应两高斯混合。然后估计从阈值较低的平均值的拟合高斯。
值----------Value----------
Single numeric value. The threshold that is the minimal data value with an adjusted p-value smaller than a specified threshold.
单一数值。阈值是最小的数据值与调整后的p值小于指定的阈值。
注意----------Note----------
Please note that the use of the package 'mclust' is only free for strict academic use (see the license of 'mclust' here: http://www.stat.washington.edu/mclust/license.txt ). The alternative function upperBoundNull does not have this restriction.
请注意，使用包mclust只适用于严格的学术用途的自由（见许可证“mclust这里：http://www.stat.washington.edu/mclust/license.txt的）。替代的功能upperBoundNull没有这种限制。
Thanks to Richard Bourgon for pointing out the necessity of providing this method as an alternative way of estimating the threshold.
感谢理查德Bourgon指出，作为替代方法估算的阈值提供这种方法的必要性。
作者（S）----------Author(s)----------
Joern Toedling, Aleksandra Pekowska
参见----------See Also----------
mclust, p.adjust, upperBoundNull
mclust，p.adjust，upperBoundNull
举例----------Examples----------
exDir <- system.file("exData",package="Ringo")
load(file.path(exDir,"exampleProbeAnno.rda"))
load(file.path(exDir,"exampleX.rda"))
smoothX <- computeRunningMedians(exampleX, probeAnno=exProbeAnno,
modColumn = "Cy5", allChr = "9", winHalfSize = 400)
## compare the two different ways of estimating the threshold[＃比较两个不同的方法估算的阈值。]
y0a <- apply(exprs(smoothX), 2, upperBoundNull)
y0b <- apply(exprs(smoothX), 2, twoGaussiansNull)
hist(exprs(smoothX)[,1], n=10, main=NA,
xlab="Smoothed expression level [log2]")
abline(v=c(y0a, y0b), col=c("blue","orange"), lwd=2)
legend(x="topright", col=c("blue","orange"), lwd=2,
legend=c(expression(paste(y[0]," Non-parametric")),
expression(paste(y[0]," Gaussian"))))
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 2012-2-26 12:59:34
