samplesize(OCplus)
samplesize()所属R语言包：OCplus
FDR as a function of sample size
FDR作为一个样本大小的功能
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function tabulates the false discovery rate (FDR) for selecting differentially expressed genes as a function of sample size and cutoff level. Additionally, the same information can be displayed through an attractive plot.
此功能列表选择样本大小的功能和截止水平的差异表达基因的错误发现率（FDR）。此外，相同的信息可以显示通过一个有吸引力的图。
用法----------Usage----------
samplesize(n = seq(5, 50, by = 5), p0 = 0.99, sigma = 1, D, F0, F1,
paired = FALSE, crit, crit.style = c("top percentage", "cutoff"),
plot =TRUE, local.show=FALSE, nplot = 100, ylim = c(0, 1), main,
legend.show = FALSE, grid.show = FALSE, ...)
参数----------Arguments----------
参数：n
sample size (as subjects per group)
样本大小（每组科目）
参数：p0
the proportion of non-differentially expressed genes
非差异表达基因的比例
参数：sigma
the standard deviation for the log expression values
log表达值的标准偏差
参数：D
assumed average log fold change (in units of sigma), by default 1; this is a shortcut for specifying a simple symmetrical alternative hypothesis through F1.
假定平均log倍（单位sigma），默认为1，这是一个快捷方式指定一个简单的对称替代假说通过F1。
参数：F0
the distribution of the log2 expression values under the null hypothesis; by default, this is normal with mean zero and standard deviation sigma, but mixtures of normals can be specified, see Details and Examples.
零假设下的log2表达式的值分布;默认情况下，这是正常的零均值和标准差sigma，但可以指定法线的混合物，看到的细节和例子。
参数：F1
the distribution of the log2 expression values under the alternative hypothesis; by default, this is an equal mixture of two normals with means D and -D and standard deviation sigma; mixture of normals are again possible, see Details and Examples.
替代假设下的log2表达值的分布;默认情况下，这是两个法线平等的混合物的手段D - D“标准偏差sigma;法线混合物再有可能，看到的细节和例子。
参数：paired
logical value indicating whether this is the independent sample case (default) or the paired sample case.
逻辑值，指出这是否是独立样本的情况下（默认）或配对样本的情况下。
参数：crit
a vector of cutoff values for selecting differentially expressed genes; the interpretation depends on crit.style.
的临界值的选择差异表达基因的向量;解释取决于crit.style。
参数：crit.style
indicates how differentially expressed genes are selected: either by a fixed cutoff level for the absolute value of the t-statistic or as a fixed percentage of the absolute largest t-statistics.
表示差异表达的基因是如何选择：要么由固定为t-统计的绝对值或作为固定百分比的绝对最大的t-统计的截止水平。
参数：plot
logical value indicating whether to do the plotting business
逻辑值，该值指示是否做策划业务
参数：local.show
logical value indicating whether to show local or global false discovery rate (default: global).
逻辑值，指明是否显示本地或全球性的错误发现率（默认是：全球）。
参数：nplot
number of points that are evaluated for the curves
曲线评估点的数量
参数：ylim
the usual limits on the vertical axis
纵轴上通常限制
参数：main
the main title of the plot
该图的主标题
参数：legend.show
logical value indicating whether to show a legend for the types of gene selection in the plot
逻辑值指示是否显示基因选择的类型中的图传奇
参数：grid.show
logical value indicating whether to draw grid lines showing the sample sizes n to be tabulated in the plot
逻辑值，该值指示是否绘制网格线显示，样本大小n要载列的图
参数：...
the usual graphical parameters, passed to plot
通常的图形参数，传递plot的
Details
详情----------Details----------
This function plots the FDR as a function of the sample size when comparing the expression of multiple genes between two groups of subjects. This is based on a model assuming that a proportion p0 of genes is not differentially expressed (regulated) between groups, and that 1-p0 genes are. The logarithmized gene expression values of regulated and non regulated genes are assumed to be generated by mixtures of normal distributions; these mixtures can be specified through the parameters F0, F1 or D, and sigma; please see TOC for details on the model and the specification of the mixtures. By default, the null distribution of the log expression values is a normal centered on zero, and the alternative an equal mixture of normals centered at +D and -D.
此功能的图作为一个样本大小的功能比较两组受试者之间的多个基因的表达时的FDR。这是基于一个假设p0基因没有差异表达（监管）群体之间，以及1比例的模型 - p0基因。基因的logarithmized规范和非调控基因的表达值被假定为正态分布的混合物产生这些混合物可以通过指定的参数F0，F1或D， sigma;请参阅TOC模型的细节和规范的混合物。默认情况下，空分布的log表达值是正常的中心，对零和替代中心法线+D和-D平等的混合物。
The list of nominally differentially expressed genes can be selected in two ways:
名义上差异表达的基因列表，可以选择在两个方面：
all genes with absolute t-statistic larger than the specified critical cutoff values (cutoff),
所有的基因，绝对比指定的关键临界值（cutoff）t-统计
all genes that represent the specified critical top percentage of the absolutely largest t-statistics (top percentage).
所有的基因代表指定的关键绝对是最大的t-统计量的百分比（top percentage）。
Multiple critical values correspond to multiple curves, each labeled by the critical value, but only one value can be specified for the proportion of non-regulated genes p0 and the standard deviation sigma.
多个临界值对应多个曲线，每个标记的临界值，但只有一个值，可以指定非调节基因的比例p0和标准偏差sigma。
值----------Value----------
A matrix with rows corresponding to elements of n and columns corresponding to the specified critical values is returned. The matrix has the attribute param that contains the specified arguments, see Examples.
一个矩阵相应n和列对应到指定的临界值的元素，具有行返回。矩阵param，包含指定参数的属性，看到的例子。
注意----------Note----------
Both the curve labels and the legend may be squashed if the plotting device is too small. Increasing the size of the device and re-plotting should improve readability.
曲线标签和图例可能是压扁的，如果打印设备太小。增加设备的大小和重新绘制应提高可读性。
作者（S）----------Author(s)----------
Y. Pawitan and A. Ploner
参考文献----------References----------
<h3>See Also</h3>
举例----------Examples----------
# Default assumes a proportion of 0.01 regulated genes equally split[默认情况下假定比例均分0.01调控基因]
# between two-fold up- and down-regulated[2倍，并下调之间]
# We select the top 1, 2, 3 percent absolute largest t-statistics[我们选择最高的1，2，3％的绝对最大的t-统计]
samplesize(crit=c(0.03,0.02, 0.01))
# Same model, but using a hard cutoff for the t-statistics[相同的模式，而是使用硬截止为t-统计]
samplesize(crit=2:4, crit.style="cutoff")
# Paired test of the same size has slightly better FDR (as expected)[大小相同的配对测试稍好FDR（如预期）]
samplesize(paired=TRUE)
# Compare the effect of p0 and effect size[比较效应和规模效应的P0]
par(mfrow=c(2,2))
samplesize(crit=c(0.03,0.02, 0.01), p0=0.95, D=1)
samplesize(crit=c(0.03,0.02, 0.01), p0=0.99, D=1)
samplesize(crit=c(0.03,0.02, 0.01), p0=0.95, D=2)
samplesize(crit=c(0.03,0.02, 0.01), p0=0.99, D=2)
# An asymmetric alternative distribution: 20 percent of the regulated genes [一个不对称的替代分布：20％的调节基因]
# are expected to be (at least) four-fold up regulated[预计将（至少）上调四倍]
# NB, no graphical output[NB，没有图形输出]
ret = samplesize(F1=list(D=c(-1,1,2), p=c(2,2,1)), p0=0.95, crit=0.05, plot=FALSE)
ret
# Look at the parameters[看参数]
attr(ret, "param")
# A wide null distribution that allows to disregard genes with small effect[宽的空分布可以无视小的影响的基因]
# Here: |log2 fold change| < 0.25, i.e. fold change of less than 19 percent[这里：| log2倍的变化<0.25倍，低于19％，即变化]
samplesize(F0=list(D=c(-0.25,0,0.25)), grid=TRUE)
# This is close to Example 3 in Jung's paper (see References):[这是接近荣格的文件（见参考资料）为例：]
# p0=0.99 and sensitivity=0.6, so we want a rejection rate of [P0 = 0.99和灵敏度= 0.6，所以我们希望有一个废品率]
# around 0.006 from the top list.[0.006左右，从顶部的列表。]
# Here we require around 40 arrays/group, compared to [在这里，我们需要约40阵列/组相比，]
# around 37 in Jung's paper, most likely because we use [荣格的文件37左右，最有可能的，因为我们使用]
# the t-distribution instead of normal. Jung's alternative [t分布，而不是正常的。荣格的替代]
# is only one-sided, so the exact correspondence is[仅仅是片面的，所以确切的对应关系是]
# []
samplesize(p0=0.99,crit.style="top", crit=0.006, F1=list(D=1, p=1), grid=TRUE)
abline(h=0.01)
#The result is very close to the symmetric alternatives: [其结果是非常接近对称的替代品：]
samplesize(p0=0.99,crit=0.006, D=1, grid=TRUE, ylim=c(0,0.9))
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 08:02:49
