R/find_top_consensus.R

In RajLabMSSM/echoannot: echoverse module: Annotate fine-mapping results

#' Find the top Consensus SNP
#'
#' Identify the \code{n_top} Consensus SNP(s) per Locus,
#' defined as the Consensus SNPs with the highest mean PP
#' across all fine-mapping tools used.
#' @keywords internal
#' @importFrom dplyr group_by arrange slice vars
find_top_consensus <- function(dat,
                               n_top = 1,
                               grouping_vars = c("Locus")) {
    mean.PP <- Consensus_SNP <- NULL;
    #### Get top consensus SNPs ####
    top.consensus <- (dat |>
        dplyr::group_by(dplyr::vars(grouping_vars)) |>
        subset(Consensus_SNP) |>
        dplyr::arrange(-mean.PP) |>
        # dplyr::arrange(-IMPACT_score) |>
        # dplyr::mutate(topConsensus = ifelse(Consensus_SNP &
        # mean.PP==max(mean.PP,na.rm = T),T,F)) |>
        dplyr::slice(n_top))$SNP |> unique()
    dat$topConsensus <- dat$SNP %in% top.consensus
    return(dat)
}