fdr2d(OCplus)
fdr2d()所属R语言包：OCplus
Compute two-dimensional local false discovery rate
计算二维局部虚假的发现率
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function calculates the local false discovery rate for a two-sample problem using a bivariate test statistic, consisting of classical t-statistics and the corresponding logarithmized standard error.
此函数计算两个样品使用一个二元的检验统计量的问题，包括经典的t-统计量和相应的标准logarithmized错误的地方错误发现率。
用法----------Usage----------
fdr2d(xdat, grp, test, p0, nperm = 100, nr = 15, seed = NULL, null = NULL,
constrain = TRUE, smooth = 0.2, verb = TRUE, ...)
参数----------Arguments----------
参数：xdat
the matrix of expression values, with genes as rows and samples as columns
矩阵表达式的值，行和列的样本的基因
参数：grp
a grouping variable giving the class membership of each sample, i.e. each column in xdat
分组给每个样品的类成员变量，即xdat的每列
参数：test
a function that takes xdat and grp as the first two arguments and returns the bivariate test statistics as two-column matrix; by default, two-sample t-statistics and logrithmized standard errors are calculated.
一个函数，它xdat和grp前两个参数并返回两列矩阵的二元测试统计，默认情况下，两样本的t-统计和logrithmized标准误差计算。
参数：p0
if supplied, an estimate for the proportion of non-differentially expressed genes; if not supplied, the routine will estimate it, see Details.
如果提供，非差异表达基因的比例估计，如果不提供，常规估计，查看详细信息。
参数：nperm
number of permutations for establishing the null distribution of the t-statistic
建立空分布的t-统计数排列
参数：nr
the number of equidistant breaks for the range of each test statistic; fdr values are calculated on the resulting (nr-1) x (nr-1) grid of cells.
每个测试的统计范围为等距截断; FDR值计算的结果（NR-1）×（NR-1）单元网格上。
参数：seed
if specified, the random seed from which the permuations are started
如果指定，从中随机种子permuations启动
参数：null
optional argument for passing in a pre-calculated null distribution, see Examples.
通过在预先计算的空分布的可选参数，看到的例子。
参数：constrain
logical value indicating whether the estimated fdr should be constrained to be monotonously decreasing with the absolute size of the t-statistic (more generally, the first test statistic).
逻辑值，指明是否估计FDR单调t-统计（更普遍的是，第一个测试统计）的绝对规模下降，应限制。
参数：smooth
a numerical value between 0.01 and 0.99, indicating which percentage of the available degrees of freedom are used for smoothing the fdr estimate; larger values indicate more smoothing.
0.01和0.99之间的数值，表明这自由的可用度的百分比用于平滑FDR估计值越大表示更平滑。
参数：verb
logical value indicating whether provide extra information.
逻辑值，该值指示是否提供额外的信息。
参数：...
extra arguments to function test.
额外的参数给函数test。
Details
详情----------Details----------
This routine computes a bivariate extension of the classical local false discovery rate as available through function fdr1d. Consequently, many arguments have identical or similar meaning. Specifically for fdr2d, nr specifies the number of equidistant breaks defining a two-dimensional grid of cells on which the bivariate test statistics are counted; argument constrain can be set to ensure that the estimated fdr is decreasing with increasing absolute value of the t-statistic; and argument smooth specifies the degree of smoothing when estimating the fdr.
这可以通过常规计算的古典本地虚假发现率的二元扩展功能fdr1d。因此，许多参数有相同或相似的意义。具体来说fdr2d，，估计nr指定等距截断的定义一个二维网格上二元测试统计计算单元的数量;参数constrain可以设置，以确保FDR随t-统计的绝对值下降;参数smooth指定估计的FDR时，平滑度。
Note that while fdr2d might be used for any suitable pair of test statistics, it has only been tested for the default pair, and the smoothing procedure specifically is optimized for this situation.
请注意，而fdr2d可能被用于任何合适的一对测试统计，仅经过测试，默认对平滑的过程，特别是针对这种情况进行了优化。
Note also that the estimation of the proportion p0 directly from the data may be quite unstable and dependant on the degree of smoothing; too heavy smoothing may even lead to estimates greater than 1. It is usually more stable use an estimate of p0 provided by fdr1d.
还要注意的是估计的比例p0直接从数据可能会相当不稳定和平滑度的依赖太重平滑，甚至可能导致估计大于1。它通常是更稳定的使用p0fdr1d的估计。
Note that fdr1d can also be used to check the degree of smoothing, see average.fdr.
注意fdr1d也可以被用来检查平滑度，看到average.fdr。
值----------Value----------
Basically, a data frame with one row per gene and three columns: tstat, the test statistic, logse, the corresponding logarithmized standard error, and fdr.local, the local false discovery rate. This data frame has the additional class attributes fdr2d.result and fdr.result, see Examples. This is the bad old S3 class mechanism employed to provide plot and summary functions.
基本上，每个基因一行三列的数据框：tstat，测试统计，logse“的相应logarithmized标准错误，和fdr.local，当地的假发现率。此数据框有额外的类属性fdr2d.result和fdr.result，看到的例子。这是坏的老S3类的机制，以提供图和汇总功能。
Additional information is provided by a param attribute, which is a list with the following entries:
param属性，这是一个具有以下条目列表提供更多的信息：
参数：p0
the proportion of non-differentially expressed genes used when calculating the fdr.
非差异表达基因的比例计算FDR时使用。
参数：p0.est
a logical value indicating whether p0 was estimated from the data or supplied by the user.
一个逻辑值，指明是否p0估计的数据，或由用户提供。
参数：fdr
the matrix of smoothed fdr values calculated on the original grid.
平滑的矩阵FDR值计算原始网格上。
参数：xbreaks
vector of breaks for the first test statistic.
第一个测试统计的中断向量。
参数：ybreaks
vector of breaks for the second test statistic.
第二次测试统计截断的向量。
作者（S）----------Author(s)----------
A Ploner and Y Pawitan
参考文献----------References----------
参见----------See Also----------
plot.fdr2d.result, summary.fdr.result, OCshow, fdr1d, average.fdr
plot.fdr2d.result，summary.fdr.result，OCshow，fdr1d，average.fdr
举例----------Examples----------
# We simulate a small example with 5 percent regulated genes and[我们模拟一个小例子，用5％的调节基因和]
# a rather large effect size[一个相当大的规模效应]
set.seed(2000)
xdat = matrix(rnorm(50000), nrow=1000)
xdat[1:25, 1:25] = xdat[1:25, 1:25] - 1
xdat[26:50, 1:25] = xdat[26:50, 1:25] + 1
grp = rep(c("Sample A","Sample B"), c(25,25))
# A default run[默认的运行]
res2d = fdr2d(xdat, grp)
res2d[1:20,]
# Looking at the results[看结果]
summary(res2d)
plot(res2d)
res2d[res2d$fdr<0.05, ]
# Extra information[额外信息]
class(res2d)
attr(res2d,"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 08:02:00
