R/krsa_filter_nonLinear.R

In CogDisResLab/KRSA: KRSA: Kinome Random Sampling Analyzer

#' Filters out peptides with none linear signals based on the pw data
#'
#' This function takes in the pw data, r2 threshold, and samples and group names (optional)
#'
#' @param data krsa modeled pw data (scaled)
#' @param threshold r2 threshold
#' @param samples (optional) sample names
#' @param groups (optional) group names
#'
#' @return vector
#'
#' @family QC functions
#'
#' @export
#'
#' @examples
#' TRUE
krsa_filter_nonLinear <- function(data, threshold, samples = NULL, groups = NULL) {
    data %>%
        {
            if (!is.null(samples)) dplyr::filter(., SampleName %in% samples) else .
        } %>%
        {
            if (!is.null(groups)) dplyr::filter(., Group %in% groups) else .
        } %>%
        dplyr::select(SampleName, Peptide, r.seq) %>%
        tidyr::spread(SampleName, r.seq) %>%
        dplyr::filter_at(vars(-Peptide), dplyr::all_vars(. >= threshold)) %>%
        dplyr::pull(Peptide) -> p



    message(paste("Filtered out", length(data$Peptide %>% unique()) - length(p), "Peptides"))

    p
}