% Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/diffHet.R
 \name{diffHet}
 \alias{diffHet}
 \title{Calculate Differential Heterogeneity}
 \usage{

 diffHet(compare.matrix, value, group1, group2, subtype,

   het.dif.cutoff = 0.2, permutations = 1000, permutationtest = FALSE,
   p.adjust.method = "fdr", cores = 5)

 }
 \arguments{
 \item{compare.matrix}{The comparison matrix generated from
 the compMatrix() function}
 
 \item{value}{The value to be used in calculations. Possible
 values are 'read', 'pdr', 'meth', 'epipoly', and 'shannon'}
 
 \item{group1}{The first subtype group to be compared}
 
 \item{group2}{The second subtype group to be compared}
 
 \item{subtype}{A dataframe containing the subtype information
 for the samples in the comparison matrix. The row names should
 be the names of the samples and there should be one column
 containing the subtype information for each sample.}
 
 \item{het.dif.cutoff}{A number representing the cutoff
 for the heterogeneity difference. If the heterogeneity difference is greater
 than the cutoff value, than the p-value and adjusted p-value are
 calculated for the loci. If the heterogeneity difference is less than
 the cutoff value, than the p-value and adjusted p-value are set
 to NA. (default: 0.20)}
 
 \item{permutations}{The number of permutations for the
 EntropyExplorer function. Value must be set to 'shannon'.
 (default: 1000)}
 

 \item{permutationtest}{boolean values determining if the permutation test is 
 applied for DEH loci identification based on customized heterogeneity metrics
 (default: FALSE)}
 

 \item{p.adjust.method}{The method to be used as a parameter in
 p.adjust() function. Possible methods are 'holm', 'hochberg',
 'hommel', 'bonferroni', 'BH', 'BY', 'fdr', and 'none'.(default: 'fdr')}
 
 \item{cores}{The number of cores to be used for parallel execution.
 Not available for 'shannon' values. (default: 5)}
 }
 \value{
 A dataframe containing chromosome number, loci, mean of
 group1, mean of group2, heterogeneity difference, and the p-value and
 adjusted p-value for the loci with a heterogeneity difference greater
 than the cutoff
 }
 \description{
 From a user-inputted value and two subtype groups,
 calculates the mean values for both subtypes at each
 loci. The heterogeneity difference is calculated and the p-values
 and adjusted p-values are calculated if the heterogeneity
 difference is greater than a given cutoff
 }