R/distance_filter.R

In comoto-pasteur-fr/DNABarcodeCompatibility: A Tool for Optimizing Combinations of DNA Barcodes Used in Multiplexed Experiments on Next Generation Sequencing Platforms

#' @title 
#' Select barcode combinations with error correction properties
#'
#' @description 
#' Filters a list of barcode combinations for a given distance metric 
#' (hamming or seqlev) and threshold in order to produce a list of barcodes
#' satisfying the distance constraints.
#'
#' @usage 
#' distance_filter(index_df, combinations_m, metric, d)
#'
#' @param index_df A dataframe containing barcodes identifiers, 
#' corresponding DNA sequences along with GC content and presence 
#' of homopolymers.
#' 
#' @param combinations_m A matrix of compatible barcode combinations.
#' @param metric The type of distance (hamming or seqlev or phaseshift).
#' @param d The minimum value of the distance.
#'
#' @details 
#' The "hamming" distance is suitable for correcting substitution errors. 
#' The "seqlev" distance is suitable for correcting both 
#' substitution and insertion/deletion errors.
#'
#' @return 
#' A filtered matrix containing the identifiers of the barcodes
#' satisfying the distance constraints.
#'
#' @examples
#' barcodes <- DNABarcodeCompatibility::IlluminaIndexes
#' m <- get_all_combinations(barcodes, 2, 4)
#' distance_filter(barcodes, m, "hamming", 3)
#'
#' @seealso 
#' \code{\link{get_all_combinations}}, 
#' \code{\link{get_random_combinations}}
#' 
#' @references Buschmann, T. 2015. 
#' The Systematic Design and Application of Robust DNA Barcodes. 
#' @references Buschmann, T. 2017. 
#' DNABarcodes: an R package for the systematic construction of 
#' DNA sample tags. Bioinformatics 33, 920–922.
#' 
#' @export
#' 

distance_filter = function(index_df, combinations_m, metric, d) {
    check_input_dataframe(  index_df, 
                            c("Id", "sequence", "GC_content", "homopolymer"))
    if (is.numeric(d)) {
        if (d <= nchar(index_df$sequence[1])){
            index_distance_df =  index_distance(index_df)
            if (metric == "hamming" || 
                metric == "seqlev" || 
                metric =="phaseshift") {
                if (metric == "hamming") {
                    hamming_rejection_table = low_hamming_distance(
                    index_df,
                    index_distance_df,
                    d)
                    filtered_combinations_m = filter_combinations(
                        combinations_m,
                        hamming_rejection_table)
                } else if (metric == "seqlev") {
                    seqlev_rejection_table = low_seqlev_distance(
                        index_df,
                        index_distance_df,
                        d)
                    filtered_combinations_m = filter_combinations(
                        combinations_m,
                        seqlev_rejection_table)
                } else if (metric == "phaseshift") {
                    phaseshift_rejection_table = low_phaseshift_distance(
                        index_df,
                        index_distance_df,
                        d)
                    filtered_combinations_m = filter_combinations(
                        combinations_m,
                        phaseshift_rejection_table)
                }
    if(nrow(filtered_combinations_m) < 1){
            display_message("No combination feats your research criteria")
            return(NULL)
        } else {
            return (filtered_combinations_m)
        }
            } else {
                display_message(paste(
                    "metric should be 'hamming',",
                    "'seqlev' or 'phaseshift'"))
                return(NULL)
            }
        } else {
            display_message("Please enter a d value <= sequence length")
            return(NULL)
        }
    } else{
        display_message("Please enter a number as d")
        return(NULL)
    }
}