genEset

a data matrix stores gene expression data. Rows are genes and columns are subjects.

a data frame stores phenotype data. Rows are subjects and columns are variables describing subjects. Row names of <code>pDat</code> must be idential to the column names of <code>ex</code>.

pDat

a data frame stores feature data. Rows are genes and columns are variables describing genes. Row names of <code>fDat</code> must be idential to the row names of <code>ex</code>.

fDat

character. indicates R Bioconductor annotation package that provides annotation for genes.

annotation

 method 

There are 6 novel robust tests for equal correlation. They are all based on logistic regressions. The score statistic U is proportion to difference of two correlations based on different types of correlation in 6 methods. The ST1() is based on Pearson correlation. ST2() improved ST1() by using median absolute deviation. ST3() utilized type M correlation and ST4() used Spearman correlation. ST5() and ST6() used two different ways to combine ST3() and ST4(). We highly recommend ST5() according to the article titled ''New Statistical Methods for Constructing Robust Differential Correlation Networks to characterize the interactions among microRNAs'' published in Scientific Reports. Please see the reference: Yu et al. (2019) <doi:10.1038/s41598-019-40167-8>.

genEset: Generate an ExpressionSet Object

Description

Usage

Arguments

Value