MethEvolSIM (version 0.2)

compute_meanCor_ni: Compute the Mean Correlation of Methylation State in Non-islands

Description

This function calculates the mean correlation of methylation states within non-island structures, allowing to exclude the shores.

Usage

compute_meanCor_ni(
  index_nonislands,
  minN_CpG,
  shore_length,
  data,
  sample_n,
  categorized_data = FALSE
)

Value

A numeric value representing the mean correlation of methylation states in the central CpGs of non-islands.

Arguments

index_nonislands

A vector containing the structural indices for non-islands.

minN_CpG

The minimum number of central CpGs required for computation.

shore_length

The number of CpGs at each side of an non-island to exclude (shores).

data

A list containing methylation states at tree tips for each genomic structure (island / non-island) For a single tip: data[[structure]]. For multiple tips: data[[tip]][[structure]]. 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

sample_n

The number of tips (samples) to process.

categorized_data

Logical defaulted to FALSE. TRUE to skip redundant categorization when methylation states are represented as 0, 0.5, and 1.

Details

The function processes only non-islands with a minimum length equal to 2 * shore_length + minN_CpG. If none has minimum length, returns NA

Examples

# Example usage:
index_nonislands <- c(1, 2)
data <- list(
  list(c(0, 1, 0.5, 1, 0.5, 0), c(0.5, 0.5, 1, 1, 0, 0)), # tip 1
  list(c(1, 0, 1, 1, 0.5, 0), c(1, 1, 0.5, 0.5, 0, 1))   # tip 2
)
minN_CpG <- 2
shore_length <- 1
sample_n <- 2
compute_meanCor_ni(index_nonislands, minN_CpG, shore_length, data, sample_n,
                    categorized_data = TRUE)