R/multiOmicsPlot_internal.R

In Miswi/RiboCrypt: Interactive visualization in genomics

#' #' @importFrom Biostrings nchar translate
#' #'
#' multiOmicsPlot_internal <- function(display_range, df, annotation = "cds",reference_sequence = findFa(df),
#'                                     reads = outputLibs(df, type = "pshifted", output.mode = "envirlist",
#'                                                        naming = "full", BPPARAM = BiocParallel::SerialParam()),
#'                                     viewMode = c("tx", "genomic")[1],
#'                                     custom_regions = NULL,
#'                                     leader_extension = 0, trailer_extension = 0,
#'                                     withFrames = libraryTypes(df, uniqueTypes = FALSE) %in% c("RFP", "RPF", "LSU"),
#'                                     frames_type = "lines", colors = NULL, kmers = NULL, kmers_type = c("mean", "sum")[1],
#'                                     ylabels = bamVarName(df), lib_to_annotation_proportions = c(0.8,0.2),lib_proportions = NULL,
#'                                     annotation_proportions = NULL,width = NULL, height = NULL,
#'                                     plot_name = "default", plot_title = NULL,
#'                                     display_sequence = c("both","nt", "aa", "none")[1], seq_render_dist = 100,
#'                                     aa_letter_code = c("one_letter", "three_letters")[1],
#'                                     annotation_names = NULL, start_codons = "ATG", stop_codons = c("TAA", "TAG", "TGA"),
#'                                     custom_motif = NULL, BPPARAM = BiocParallel::SerialParam(),
#'                                     input_id = "", summary_track = FALSE,
#'                                     summary_track_type = frames_type, export.format = "svg") {
#'
#'   multiOmicsController()
#'   # Get NGS data tracks
#'   force(display_range)
#'   force(kmers_type)
#'   force(frames_type)
#'   force(reads)
#'   force(withFrames)
#'   force(kmers)
#'   if (is(BPPARAM, "SerialParam")) {
#'     profiles <- mapply(function(x,y,c) getProfileWrapper(display_range, x,y,c,kmers_type, type = frames_type),
#'                        reads, withFrames, kmers, SIMPLIFY = FALSE)
#'   } else {
#'     profiles <- bpmapply(function(x,y,c) getProfileWrapper(display_range, x,y,c,kmers_type, type = frames_type),
#'                          reads, withFrames, kmers, SIMPLIFY = FALSE, BPPARAM = BPPARAM)
#'   }
#'
#'   # Get sequence and create basic seq panel
#'   target_seq <- extractTranscriptSeqs(reference_sequence, display_range)
#'   seq_panel_hits <- createSeqPanelPattern(target_seq[[1]], start_codons = start_codons,
#'                               stop_codons = stop_codons, custom_motif = custom_motif)
#'   seq_panel <- plotSeqPanel(seq_panel_hits, target_seq[[1]])
#'
#'   # Get the panel for the annotation track
#'   gene_model_panel <- createGeneModelPanel(display_range, annotation,
#'                                            custom_regions = custom_regions,
#'                                            viewMode = viewMode)
#'   lines <- gene_model_panel[[2]]
#'   gene_model_panel <- geneModelPanelPlot(gene_model_panel[[1]])
#'
#'
#'   #browser()
#'   force(colors)
#'   force(lines)
#'   force(ylabels)
#'   total_libs <- length(profiles)
#'   if (is(BPPARAM, "SerialParam")) {
#'     plots <- mapply(function(x,y,z,c,d) createSinglePlot(x,y,z,c,d, lines, type = frames_type, total_libs),
#'                     profiles, withFrames, colors, ylabels, ylabels_full_name,
#'                     SIMPLIFY = FALSE)
#'   } else {
#'     plots <- bpmapply(function(x,y,z,c,d) createSinglePlot(x,y,z,c,d, lines, type = frames_type, total_libs),
#'                       profiles, withFrames, colors, ylabels, ylabels_full_name,
#'                       SIMPLIFY = FALSE, BPPARAM = BPPARAM)
#'   }
#'   nplots <- length(plots)
#'   if (summary_track) {
#'     nplots <- nplots + 1
#'     plots <- make_summary_track(profiles, plots, withFrames, colors,
#'                                 lines, summary_track_type, nplots)
#'   }
#'
#'   without_sequence_track <- display_sequence %in% c("none", FALSE)
#'   if (without_sequence_track) { # plotly subplot without sequence track
#'     nplots <- nplots+ 2
#'     plots <- c(plots, list(automateTicksGMP(gene_model_panel), automateTicksX(seq_panel)))
#'   } else { # plotly subplot with sequence track
#'     nplots <- nplots + 3
#'     plots <- c(plots, list(automateTicks(nt_area_template()), automateTicksGMP(gene_model_panel),
#'                            automateTicksX(seq_panel)))
#'   }
#'   # browser()
#'   plots <- lapply(plots, function(x) x  %>% layout(xaxis = list(title = list(font = list(size = 22)), tickfont = list(size = 16)),
#'                                                    yaxis = list(title = list(font = list(size = 22)), tickfont = list(size = 16)) ))
#'   multiomics_plot <- subplot(plots,
#'                              margin = 0,
#'                              nrows = nplots,
#'                              heights = proportions,
#'                              shareX = TRUE,
#'                              titleY = TRUE, titleX = TRUE)
#'   if (!without_sequence_track) {
#'     multiomics_plot <- addJSrender(multiomics_plot, target_seq, nplots-3, seq_render_dist,
#'                                    display_dist, aa_letter_code, input_id)
#'   }
#'
#'   filename <- ifelse(plot_name == "default", names(display_range), plot_name)
#'   multiomics_plot <- addToImageButtonOptions(multiomics_plot, filename,
#'                                          width, height, format = export.format)
#'   if (!is.null(plot_title)) multiomics_plot <- multiomics_plot %>% plotly::layout(title = plot_title)
#'
#'   return(multiomics_plot)
#' }