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Calculate the Number of Crossovers

Usage

calculate_crossovers(individual_df, n_trials, n_replicates)

Arguments

individual_df

A data frame containing the individual dataset.

n_trials

The total number of trials in the dataset (the number of rows)

n_replicates

The total number of replicates in each trial (the number of columns - 2)

Value

The number of crossovers detected in the dataset.

Details

This function calculates the number of crossovers in a dataset by comparing the values of replicates across multiple trials. It assumes that missing values (NAs) have been interpolated using the clean_data function.

See also

clean_data for information on data cleaning.

Examples

data <- matrix(
   c(
     1, 60, 1, 2, 3, 4, 5,   # No NA values
     1, 90, 9, NA, 4, NA, 2,  # NA Values in row
     1, 120, 3, 6, NA, NA, 9  # Consecutive NA values
    ),
    nrow = 3,
    byrow=TRUE
)
n_trials <- nrow(data)
n_replicates <- ncol(data) - 2
crossovers <- calculate_crossovers(data, n_trials, n_replicates)
cat("Number of crossovers:", crossovers, "\n")
#> Number of crossovers: 14