R/kznfsComplexHeatmap.R

In ferygood/twice: A collections of useful functions to analyze transcription factors and transposable elements data

#' Use ComplexHeatmap to visualize KZNFs data from TEKRABber result
#' @description This function use ComplexHeatmap::Heatmap() to visualize KZNFs
#' data generated from using TEKRABber. First it will load the built-in
#' hmKZNFs337 and filter the dataframe. The dataframe is the file with
#' extension geneDESeq2norm.csv from TEKRABber. You can specified how many of
#' the KZNFs you want to visualize. The default is showing the top 40 KZNFs
#' with the highest row means among all samples. If you face an error with
#' could not find function "unit", you need to load the ComplexHeatmap library
#' to your workspace.
#' @param df a TEKRABber geneDESeq2norm table
#' @param top a numeric value to show top number of genes in heatmap
#' @param species indicate the species name to convert ID
#' @param fileName the name for saving pdf file (if specified)
#' @param orderMean specify if you want to order the rows based on row means
#' @param speciesAnnot a vector containing species information if you want to
#' add top annotation on your heatmap
#'
#' @importFrom grid gpar
#' @importFrom circlize colorRamp2
#' @return a ComplexHeatmap heatmap (Formal class Heatmap)
#' @export
#'
#' @examples
#' data(hmchimpGene)
#' annot <- c("Hs", "Hs", "Hs", "Pt", "Pt", "Pt")
#' kznfsComplexHeatmap(hmchimpGene, top=40, species="hsapiens",
#'                     speciesAnnot=annot)
#'
#'
kznfsComplexHeatmap <- function(df, top=40, species = "hsapiens",
                                fileName=NULL, orderMean = FALSE,
                                speciesAnnot=NULL) {

    # this is a prototype, parameters can be added later
    data(hmKZNFs337)
    df_KZNFs <- df[rownames(df) %in% hmKZNFs337$ensembl_gene_id, ]

    if (orderMean==TRUE){
        if (top >= nrow(df_KZNFs)) {
            df_KZNFs <- df_KZNFs[order(rowMeans(df_KZNFs), decreasing = TRUE), ]
        } else if (is.numeric(top) & top > 0) {
            df_KZNFs <- df_KZNFs[order(rowMeans(df_KZNFs), decreasing = TRUE), ]
            df_KZNFs <- df_KZNFs[seq_len(top), ]
        }
    }

    mat_df <- ensIDtoName(df_KZNFs, species)

    # col_fun <- colorRamp2(
    #     c(0, 4, 8),
    #     c("#33FF99", "#0000FF", "#CC3300"))

    species_ha <- NULL

    if(!is.null(speciesAnnot)) {
        species_ha = ComplexHeatmap::HeatmapAnnotation(species=speciesAnnot)
    }

    g <- ComplexHeatmap::Heatmap(
        mat_df,
        cluster_columns = FALSE,
        cluster_rows = FALSE,
        name = "Expr.",
        width = ncol(mat_df) * unit(4, "mm"),
        height = nrow(mat_df) * unit(4, "mm"),
        column_names_rot = 45,
        row_names_gp = gpar(fontsize = 8),
        column_names_gp = gpar(fontsize = 8),
        rect_gp = gpar(col = "black", lwd = 0.8),
        top_annotation = species_ha
        #col = col_fun
    )

    # save file in pdf format if fileName is specified
    if (!is.null(fileName)) {
        tidyHeatmap::save_pdf(
            g,
            filename = fileName,
            width = 8.27,
            height = 11.69
        )
    }

    g

}