mostSimilarTwo(clippda)
mostSimilarTwo()所属R语言包:clippda
A function which indentifies two columns of a matrix, or dataframe,
函数indentifies两列的矩阵,或dataframe,
译者:生物统计家园网 机器人LoveR
描述----------Description----------
A common practice in the analysis of repeated mass spectrometry data is to average the replicate expression values, a method which is only valid if there is some coherence in the peak information across replicates. The function mostSimilarTwo identifies the two columns of a matrix (or a dataframe) with the highest pairwise positive correlations. The most highly correlated replicates contain the most similar compounds.
一个常见的做法是在重复的质谱数据分析平均复制表达式的值,如果有一些在整个复制的高峰信息的连贯性,这是唯一有效的方法。的功能mostSimilarTwo标识成对最高的正相关矩阵的两列(或dataframe)。最高度相关的复制包含最类似的化合物。
用法----------Usage----------
mostSimilarTwo(Mat)
参数----------Arguments----------
参数:Mat
A dataframe, with the columns being the variables of interest, for example the spectra.
与列利益的变量,例如光谱,dataframe。
Details
详情----------Details----------
The main application of this function is in the pre-processing of mass spectrometry data. In a mass spectrometry experiment, it often happens that there is mislabelling of samples, which results in some replicates being assigned to the wrong sample class. This function sifts through this data to identify the two spectra with the most coherent signal information between them. Thus, its function has the potential to help in reducing the number of false-positive discoveries. Its other application is in the reduction of the number of replicates to two, which are then analysed using tools for duplicate peak (or gene) expression data.
此功能的主要应用是在质谱数据的前处理。在质谱实验中,它经常发生,有误报的样本,导致一些重复被分配到了错误的示例类。此功能通过这些数据进行筛选,以确定它们之间的最连贯的信号信息的两个光谱。因此,它的功能有可能帮助减少假阳性发现。它的其他应用程序是在复制的数量减少到两个,然后再重复峰值(或基因)的表达数据分析工具。
值----------Value----------
It returns a vector with two elements, being the column indices for the two most correlated variables.
它返回有两个元素,一个向量,最相关的两个变量的列索引。
作者(S)----------Author(s)----------
Stephen Nyangoma
参考文献----------References----------
举例----------Examples----------
n <- 10
Mat <- data.frame(x1=rnorm(n, mean = 0, sd = 1),x2=rnorm(n, mean = 0, sd = 3),x3=rnorm(n, mean = 1, sd = 1),x4=
rnorm(n,mean=2,sd=2))
mostSimilarTwo(Mat)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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