cor.balance(CORREP)
cor.balance()所属R语言包:CORREP
Multivariate Correlation Estimator (Equal Number of Replicates)
多元相关估计(相同数量的复制)
译者:生物统计家园网 机器人LoveR
描述----------Description----------
cor.balance estimates correlation matrix from replicated data assuming equal number of replicates. The data must be formatted in the right format (rows correspond to replicates, columns correspond to conditions, see example below) and the variance of each row of the data MUST equal to 1 (see example below).
cor.balance估计,假设复制同等数量的复制数据的相关矩阵。被格式化的数据必须在正确的格式(行对应复制,列对应的条件,见下面的例子),每一行数据的方差必须等于1(见下面的例子)。
用法----------Usage----------
cor.balance(x, m, G)
参数----------Arguments----------
参数:x
data matrix, column represents samples (conditions), and row represents variables (genes), see example below for format information
数据矩阵,列代表样本(条件),行代表变量(基因),见下面的例子的格式信息
参数:m
number of replicates for each variable (gene)
数量为每个变量的复制(基因)
参数:G
number of variables (genes)
变量(基因)
Details
详情----------Details----------
The multivariate correlation estimator assumes replicated omics data are iid samples from the multivariate normal distribution. It is derived by maximizing the likelihood function. Note that each off-diagonal element in the returned correlation matrix (G by G) is the average of off-diagonals of MLE of correlation matrix of a pair of variables (m by m).
多元相关估计,假设复制组学数据是独立同分布多元正态分布的样本。它是派生的似然函数最大化。请注意,在返回的相关矩阵(由G G)的每个非对角线元素是平均相关矩阵的一对变量(由M M)MLE对角线。
值----------Value----------
A correlation matrix estimated for G variables (genes)
估计相关矩阵为G变量(基因)
作者(S)----------Author(s)----------
Dongxiao Zhu and Youjuan Li
参考文献----------References----------
参见----------See Also----------
cor.balance, cor
cor.balance,cor
举例----------Examples----------
library("CORREP")
d0 <- NULL
for(l in 1:10)
d0 <- rbind(d0, rnorm(100))
## The simulated data corresponds to the real-world data of 25 genes and 10 conditions, each gene expression[#模拟数据对应的25个基因和10条件的真实世界的数据,每一个基因的表达]
## profiles was replicated 4 times.[#配置文件被复制的4倍。]
d0<- t(d0)
## This step is to make the standard deviation of each replicate equals to 1[#这一步是使每个复制的标准差等于1]
## so that we can model the covariance matrix as correlation matrix.[#所以,我们可以模拟相关矩阵的协方差矩阵。]
d0.std <- apply(d0, 1, function(x) x/sd(x))
M <- cor.balance(t(d0.std), m=4, G=25)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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