TOC(OCplus)
TOC()所属R语言包：OCplus
Theoretical FDR and sensitivity as a function of cutoff level
理论FDR和敏感性作为截止一级功能
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes and plots the operating characteristics for a two group microarray experiment based on a theoretical model. The false discovery rate (FDR) is plotted against the cutoff level on the t-statistic. Optionally, curves for the the classical significance level and sensitivity can be added. Different curves for different proportions of non-differentially expressed genes can be compared in the same plot, and the sample size per group can be varied between plots.
计算和绘图为两个组芯片实验的理论模型为基础的经营特色。虚假的发现率（FDR）绘制对t-统计的截止水平。或者，古典意义和灵敏度曲线可以加入。可以为不同比例的非差异表达的基因的不同曲线相比，在相同的图，每个组的样本大小图之间可以多种多样。
用法----------Usage----------
TOC(n = 10, p0 = 0.95, sigma = 1, D, F0, F1, n1 = n, n2 = n, paired = FALSE,
plot = TRUE, local.show=FALSE, alpha.show = TRUE, sensitivity.show = TRUE,
nplot = 100, xlim, ylim = c(0, 1), main, legend.show = FALSE, ...)
参数----------Arguments----------
参数：n, n1, n2
number of samples per group, by default equal and specified via n, but can be set to different values via n1 and n2.
每组样本数，默认情况下，平等，通过n指定，但可以设置不同的价值观，通过n1和n2。
参数：p0
the proportion of not differentially expressed genes, may be vector valued
没有差异表达基因的比例，可能会向量值
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 two distinct groups of observations or one group of paired observations are studied.
逻辑值，该值指示是否两个不同群体的意见或一组配对的意见进行了研究。
参数：plot
logical value indicating whether the results should be plotted.
逻辑值指示是否应绘制结果。
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：alpha.show
logical value indicating whether to show the classical significance level for testing one hypothesis as a function of the cutoff level.
逻辑值，该值指示是否显示截止水平的功能测试一个假设的古典意义水平。
参数：sensitivity.show
logical value indicating whether to show the classical sensitivity for testing one hypothesis as a function of the cutoff level.
逻辑值，该值指示是否显示截止水平的功能测试一个假设的古典灵敏度。
参数：nplot
number of points that are evaluated for the curves
曲线评估点的数量
参数：xlim
the usual limits on the horizontal axis
横轴上通常限制
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 different types of curves in the plot.
逻辑值，该值指示是否显示曲线中的图不同类型的一个传奇。
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 cutoff level when comparing the expression of multiple genes between two groups of subjects. We study a gene selection mechanism that declares all genes to be differentially expressed whose t-statistics have an absolute value greater than a specified cutoff value. The comparison is based on a two-sample t-statistic for equal variances, for either paired or unpaired observations.
截止水平的功能，此功能图FDR时，比较两组受试者之间的多个基因的表达。我们研究基因选择机制，宣布所有差异表达基因的t-统计量的绝对值大于指定的临界值。比较两个样本的T-统计方差相等，要么成对或不成对观测的基础上。
The underlying model assumes that a proportion p0 of genes are not differentially expressed between groups, and that 1-p0 are. The logarithmized gene expression values are assumed to be generated by mixtures of normal distributions. Both null and alternative hypothesis are specified through the means of the respective mixture components; these means can be interpreted as average log2 fold changes in units of the standard deviation sigma.
假定的比例p0基因没有差异表达群体之间，并有1 - p0是底层模型。 logarithmized基因表达值被假定为正态分布的混合物产生。指定null和替代假说，通过各自的混合组件的手段，这些手段可以解释为平均log2倍标准差sigma单位。
Note that the model does not assume that all genes have the same standard deviation sigma, only that the mean log2 fold change for all regulated genes is proportional to their individual variability (standard deviation). sigma generally does not need to be specified explicitly and can be left at its default value of one, so that D can be interpreted straightforward as log2 fold change between groups.
请注意，该模型不承担所有的基因有相同的标准差sigma，只有平均的log2倍，所有调节基因变化是成正比的个体差异（标准差）。 sigma一般不需要明确指定可以留在其默认值，所以D可以解释为log2群体之间的倍数变化简单。
The default null distribution of the log2 expression values is a single normal distribution with mean zero (and standard deviation sigma); the default alternative distribution is is an equal mixture of two normals with means D and -D (and again standard deviation sigma). However, general mixtures of normals can be specified for both null and alternative distribution through F0 and F1, respectively: both are lists with two elements:
默认空分布的log2表达式的值是一个单一的均值为零的正态分布（标准偏差sigma），默认的替代分布是两个法线与平等的混合物手段D - D（又一次标准偏差sigma）。然而，一般正常人的混合物可以被指定为null和替代通过F0和F1，分别分布：两者是两个元素的列表：
D is the vector of means (i.e. log2 fold changes),
D向量的手段（即log2倍变化），
p is the vector of mixing proportions for the means.
p向量为手段的混合比例。
If present, p must be the same length as D; its elements do not need to be normalized, i.e. sum to one; if absent, equal mixing is assumed, see Examples. A wide (mixture) null hypothesis, or an empirical null hypothesis as outlined by Efron (2004), can be used if genes with log fold changes close to zero are thought to be of no biological interest, and are counted as effectively not regulated. Similarly, the alternative hypothesis can be any mixture of large and small effects, symmetric or non-symmetric, depending on the expected regulation patterns, see Examples.
如果存在，p必须是相同长度的D;其元素不需要归一，即一个总和;如果缺席，等于混合假设，看到的例子。宽（混合物）的零假设，或经验的零假设埃弗龙（2004）所述，可以使用log接近于零倍变化的基因被认为是没有生物的兴趣，并计数，如不有效监管。同样，另一种假设可以是任何大型和小型的影响，对称还是非对称的混合物，根据预期的监管模式，看到的例子。
As a consequence, both the null distribution of the t-statistics (for the unregulated genes) and their alternative distribution (for the regulated genes) are mixtures of (generally non-central) t-distributions, see FDR.
作为一个后果，都空分布的t-统计（无管制的基因）和其他分销（调节基因）（一般非中心）T-分布的混合物，看到FDR。
Sample size n and standard deviation sigma are atomic values, but multiple p0 can be specified, resulting in multiple curves. Additionally, the usual significance level and sensitivity for a classical one-hypothesis can be displayed.
样本大小n和标准偏差sigma是原子值，但可以指定多个p0，造成多条曲线。此外，通常意义的水平和古典假设的敏感性可以显示。
值----------Value----------
This function returns invisibly a data frame with nplot rows whose columns contain the information for the individual curves. The number of columns and their names will depend on the number and value of the p0 specified, and whether alpha and sensitivity are displayed. Additionally, the returned data frame has an attribute param, which is a list with all the non-plotting arguments to the function.
这个函数返回无形与nplot行的列中包含的信息为个人曲线的数据框。列，他们的名字将取决于p0指定的数量和价值，以及是否显示α和灵敏度。此外，传回的数据框属性param，这是一个与所有非绘图参数的功能列表。
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----------
参见----------See Also----------
FDR, samplesize, EOC
FDR，samplesize，EOC
举例----------Examples----------
# Default null and alternative distributions, assuming different proportions[默认空和替代分布，假设不同比例]
# of regulated genes[调节基因]
TOC(p0=c(0.90, 0.95, 0.99), legend.show=TRUE)
# The effect of sample size and effect size[样本大小和规模效应的影响]
par(mfrow=c(2,2))
TOC(p0=c(0.90, 0.95, 0.99), n=5, D=1)
TOC(p0=c(0.90, 0.95, 0.99), n=30, D=1)
TOC(p0=c(0.90, 0.95, 0.99), n=5, D=2)
TOC(p0=c(0.90, 0.95, 0.99), n=30, D=2)
# A wide null distribution that allows to disregard genes of small effect[宽的空分布，可以无视小作用的基因]
# unspecified p means equal mixing proportions[未指定p表明平等的混合比例]
ret = TOC(F0=list(D=c(-0.25,0,0.25)), main="Wide F0")
attr(ret,"param")$F0 # the null hypothesis[虚无假设]
# An extended (and unsymmetric) alternative[一个扩展（非对称）替代]
ret = TOC(F1=list(D=c(-2,-1,1), p=c(1,2,2)), p0=0.95, main="Unsymmetric F1")
attr(ret,"param")$F1 # F1$p is normalized[F1 $ P归]
# Unequal sample sizes[不平等的样本大小]
TOC(n1=10, n2=30)
# Curves for a paired t-test[曲线配对t检验]
TOC(paired=TRUE)
# The output contains all the x- and y-coordinates[输出包含所有的x和y坐标]
ret = TOC(p0=c(0.90, 0.95, 0.99), main="Default settings")
dim(ret)
colnames(ret)
ret[1:10,]
# Additionally, the list of arguments that determine the experiment[此外，确定实验参数列表]
attr(ret,"param")
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 08:03:27
