mean_CherryFreqsChange_i: Mean Number of Significant Methylation Frequency Changes per...

In MethEvolSIM: Simulate DNA Methylation Dynamics on Different Genomic Structures along Genealogies

Mean Number of Significant Methylation Frequency Changes per Island in Cherries

Description

Computes the mean number of significant changes per island in phylogenetic tree cherries, based on a specified p-value threshold.

Usage

mean_CherryFreqsChange_i(
  data,
  categorized_data = FALSE,
  index_islands,
  tree,
  pValue_threshold
)

Arguments

data	A list containing methylation states at tree tips for each genomic structure (e.g., island/non-island). The data should be structured as data[[tip]][[structure]], where each structure has the same number of sites across tips. The input data must be prefiltered to ensure CpG sites are represented consistently across different tips. Each element contains the methylation states at the sites in a given tip and structure represented as 0, 0.5 or 1 (for unmethylated, partially-methylated and methylated). If methylation states are not represented as 0, 0.5, 1 they are categorized as 0 when value equal or under 0.2 0.5 when value between 0.2 and 0.8 and 1 when value over 0.8. For customized categorization thresholds use categorize_siteMethSt
categorized_data	Logical defaulted to FALSE. TRUE to skip redundant categorization when methylation states are represented as 0, 0.5, and 1.
index_islands	A numeric vector specifying the indices of islands to analyze.
tree	A rooted binary tree in Newick format (character string) or as an ape phylo object.
pValue_threshold	A numeric value between 0 and 1 that serves as the threshold for statistical significance in the chi-squared test.

Details

The function uses simulate.p.value = TRUE in chisq.test to compute the p-value via Monte Carlo simulation to improve reliability regardless of whether the expected frequencies meet the assumptions of the chi-squared test (i.e., expected counts of at least 5 in each category).

Value

A data frame containing the same information as pValue_CherryFreqsChange_i, but with additional columns indicating whether p-values are below the threshold (significant changes) and the mean frequency of significant changes per island.

Examples

tree <- "((d:1,e:1):2,a:2);"
data <- list(
  #Tip 1
  list(c(rep(1,9), rep(0,1)), 
       c(rep(0,9), 1), 
       c(rep(0,9), rep(0.5,1))), 
  #Tip 2
  list(c(rep(0,9), rep(0.5,1)), 
       c(rep(0.5,9), 1), 
       c(rep(1,9), rep(0,1))), 
  #Tip 3
  list(c(rep(1,9), rep(0.5,1)), 
       c(rep(0.5,9), 1), 
       c(rep(0,9), rep(0.5,1)))) 

index_islands <- c(1,3)
mean_CherryFreqsChange_i(data, categorized_data = TRUE,
                          index_islands, tree, pValue_threshold = 0.05)

MethEvolSIM documentation built on April 12, 2025, 1:30 a.m.