Output_cn_plots_restyling

bin/plot_wisecondorx_cnv.R

@@ -0,0 +1,159 @@
+#!/usr/bin/env Rscript
+
+suppressPackageStartupMessages({
+  library(argparser)
+  library(readr)
+  library(dplyr)
+  library(ggplot2)
+})
+
+## arguments
+
+p <- arg_parser("Plot WisecondorX output (bin-level log2 ratio + segments)")
+p <- add_argument(p, "--id", help = "Sample ID")
+p <- add_argument(p, "--seg_file", help = "Segmented file with calls from WisecondorX", nargs = Inf)
+p <- add_argument(p, "--binfile", help = "Bin-level file from WisecondorX")
+p <- add_argument(p, "--outdir", help = "Output directory", default = ".")
+p <- add_argument(p, "--ratio_limit", help = "Log2ratio limit of additional WisecondorX plots (application-generated plots are unaffected)", default = 1)
+argv <- parse_args(p)
+
+sample_id      <- argv$id
+bin_path       <- argv$binfile
+output_dir     <- argv$outdir
+ratio_limit    <- argv$ratio_limit
+
+# take the right seg_file pattern
+seg_candidates <- argv$seg_file
+if (length(seg_candidates) > 1) {
+  seg_candidates <- seg_candidates[!grepl("_gistic\\.seg$", seg_candidates)]
+}
+seg_path <- seg_candidates[1]
+
+dir.create(output_dir, showWarnings = FALSE, recursive = TRUE)
+
+
+# Fix column names
+read_and_normalize <- function(path) {
+  df <- read_tsv(path, show_col_types = FALSE) %>%
+    rename_with(tolower)
+
+  if ("chrom" %in% names(df)) df <- rename(df, chr = chrom)
+  if ("seg.mean.adj" %in% names(df)) df <- rename(df, ratio = `seg.mean.adj`)
+
+  df
+}
+
+# Remap WisecondorX gain/loss/neut calls to readable labels for the plot
+
+classify_segments <- function(df) {
+  call_map <- c(gain = "GAIN", loss = "LOSS", neut = "NEUTRAL")
+  df %>% mutate(call = recode(tolower(call), !!!call_map, .default = "NEUTRAL"))
+}
+
+# Plot style formatting, genomic coordinates
+compute_genomic_coords <- function(bins, segs) {
+  chr_order <- c(as.character(1:22), "X", "Y")
+  present_chr <- intersect(chr_order, unique(c(bins$chr, segs$chr)))
+
+  chr_lengths <- bins %>%
+    filter(chr %in% present_chr) %>%
+    group_by(chr) %>%
+    summarise(len = max(end), .groups = "drop") %>%
+    mutate(chr = factor(chr, levels = present_chr)) %>%
+    arrange(chr) %>%
+    mutate(offset = lag(cumsum(len), default = 0))
+
+  add_offset <- function(df) {
+    df %>%
+      filter(chr %in% present_chr) %>%
+      mutate(chr = factor(chr, levels = present_chr)) %>%
+      left_join(chr_lengths %>% select(chr, offset), by = "chr") %>%
+      mutate(start_g = start + offset, end_g = end + offset)
+  }
+
+  list(
+    bins = add_offset(bins) %>% mutate(pos_g = (start_g + end_g) / 2),
+    segs = add_offset(segs),
+    chr_lengths = chr_lengths %>% mutate(xmax = offset + len)
+  )
+}
+
+# Plot wisecondorx plot
+plot_wisecondorx_cnv <- function(bins, segs, chr_lengths, sample_id, ratio_limit, output_dir) {
+  chr_ticks <- chr_lengths %>% mutate(mid = offset + len / 2)
+  chr_boundaries <- chr_lengths$xmax[-nrow(chr_lengths)]
+
+  color_mapping <- c(
+    "NEUTRAL" = "#377eb8",
+    "GAIN" = "#e41a1c",
+    "LOSS" = "#4daf4a"
+  )
+
+  p <- ggplot() +
+    geom_vline(xintercept = chr_boundaries, color = "grey85", linewidth = 0.4, linetype = "dotted") +
+    geom_hline(yintercept = 0, color = "grey75", linewidth = 0.4) +
+    geom_point(
+      data = bins,
+      aes(x = pos_g, y = pmin(pmax(ratio, -ratio_limit), ratio_limit)),
+      color = "grey75", size = 0.25, alpha = 0.35
+    ) +
+    geom_segment(
+      data = segs,
+      aes(x = start_g, xend = end_g, y = ratio, yend = ratio, color = call),
+      linewidth = 1.6, lineend = "round"
+    ) +
+    scale_color_manual(
+      values = color_mapping,
+      name = "Copy Number Call",
+      guide = guide_legend(override.aes = list(linewidth = 4))
+    ) +
+    scale_x_continuous(breaks = chr_ticks$mid, labels = chr_ticks$chr, expand = c(0.01, 0.01)) +
+    scale_y_continuous(limits = c(-ratio_limit, ratio_limit)) +
+    labs(
+      x = "Chromosome", y = expression(log[2](ratio)),
+      title = paste0("Copy Number Profile", if (!is.null(sample_id)) paste0(" - ", sample_id) else "")
+    ) +
+    theme_minimal(base_size = 13) +
+    theme(
+      panel.grid.minor = element_blank(),
+      panel.grid.major.x = element_blank(),
+      panel.grid.major.y = element_line(color = "grey93", linewidth = 0.3),
+      panel.background = element_rect(fill = "white", color = NA),
+      plot.background = element_rect(fill = "white", color = NA),
+      axis.text = element_text(color = "grey30"),
+      axis.title = element_text(color = "grey20"),
+      plot.title = element_text(face = "bold"),
+      plot.subtitle = element_text(color = "grey40", size = 10),
+      legend.position = "bottom",
+      legend.title = element_text(face = "bold")
+    )
+
+  out_png <- file.path(output_dir, paste0(sample_id, ".copy_number.png"))
+  out_svg <- file.path(output_dir, paste0(sample_id, ".copy_number.svg"))
+  ggsave(out_png, plot = p, width = 14, height = 6, dpi = 300)
+  ggsave(out_svg, plot = p, width = 14, height = 6)
+  message("Plot (PNG) saved to: ", out_png)
+  message("Plot (SVG) saved to: ", out_svg)
+}
+
+# ---- main -------------------------------------------------------------
+
+message("Processing sample: ", sample_id)
+
+bins <- read_and_normalize(bin_path) %>%
+  filter(!is.na(ratio))
+segs <- read_and_normalize(seg_path) %>%
+  classify_segments()
+
+message("Data loaded - Bins: ", nrow(bins), " Segments: ", nrow(segs))
+
+coords <- compute_genomic_coords(bins, segs)
+
+plot_wisecondorx_cnv(coords$bins,
+                     coords$segs,
+                     coords$chr_lengths,
+                     sample_id,
+                     ratio_limit,
+                     output_dir)
+
+message("Plot generation completed!")

conf/modules.config

@@ -328,11 +328,10 @@ process {
 
     withName: PLOT_ICHORCNA {
         publishDir = [
-            path: { "${params.outdir}/ichorcna/corrected_plots" },
+            path: { "${params.outdir}/ichorcna/plot_cnv" },
             mode: params.publish_dir_mode,
             saveAs: { filename -> filename.equals('versions.yml') ? null : filename },
         ]
-        ext.when   = params.ichorcna_ploidy_aware_plot
     }
 
     withName: FORMAT_ICHORCNA_SEG {
@@ -402,6 +401,18 @@ process {
         ].join(' ')
     }
 
+    withName: PLOT_WISECONDORX_CNV {
+        publishDir = [
+            path: { "${params.outdir}/wisecondorx/plot_cnv" },
+            mode: params.publish_dir_mode,
+            saveAs: { filename -> filename.equals('versions.yml') ? null : filename },
+        ]
+        ext.args = [
+            params.wisecondorx_plot_y_max ? "--ratio_limit ${params.wisecondorx_plot_y_max}" : ""
+        ].join(' ')
+
+    }
+
     withName: CONVERT_GISTIC_SEG {
         publishDir = [
             path: { "${params.outdir}/wisecondorx/${meta.id}" },

modules/local/plot_wisecondorx_cnv/main.nf

@@ -0,0 +1,43 @@
+process PLOT_WISECONDORX_CNV {
+    tag "Plotting WisecondorX results for $meta.id"
+    label 'process_low'
+    container "community.wave.seqera.io/library/procps-ng_r-argparser_r-dplyr_r-ggplot2_pruned:10da72fa04bcba1a"
+
+    input:
+        tuple val(meta), path(seg_file)
+        tuple val(meta2), path(bins)
+
+    output:
+        tuple val(meta), path("*.copy_number.png"), emit: plot_png
+        tuple val(meta), path("*.copy_number.svg"), emit: plot_svg
+        path "versions.yml"                       , emit: versions
+
+    when:
+        task.ext.when == null || task.ext.when
+
+    script:
+        def args    = task.ext.args ?: ''
+        def prefix  = task.ext.prefix ?: "${meta.id}"
+        def VERSION = '0.1'
+        """
+        plot_wisecondorx_cnv.R \\
+            --id ${prefix} \\
+            --seg_file ${seg_file} \\
+            --binfile ${bins} \\
+            --outdir . \\
+            ${args}
+
+        cat <<-END_VERSIONS > versions.yml
+        "${task.process}":
+            plot_wisecondorx_cnv: $VERSION
+        END_VERSIONS
+        """
+
+    stub:
+        def prefix = task.ext.prefix ?: "${meta.id}"
+        """
+        touch ${prefix}.copy_number.png
+        touch ${prefix}.copy_number.svg
+        touch versions.yml
+        """
+}

nextflow.config

@@ -97,7 +97,6 @@ params {
     ichorcna_reptime_wig              = null
     // FIXME: Supply it with the pipeline
     ichorcna_centromere_file          = null
-    ichorcna_ploidy_aware_plot        = false
 
 
     // WisecondorX
@@ -107,6 +106,7 @@ params {
     wisecondorx_ylim                  = null
     wisecondorx_zscore                = 5
     wisecondorx_blacklist             = null
+    wisecondorx_plot_y_max    = 1
 
     // ASCAT.sc
 

nextflow_schema.json

@@ -537,10 +537,6 @@
                     "hidden": true,
                     "description": "Path to a file with centromere data for the specified genome.",
                     "format": "file-path"
-                },
-                "ichorcna_ploidy_aware_plot": {
-                    "type": "boolean",
-                    "description": "Ploidy-aware ichorCNA plots."
                 }
             }
         },
@@ -572,6 +568,11 @@
                 "wisecondorx_ylim": {
                     "type": "string",
                     "description": "Y axis limits for the generated plots"
+                },
+                "wisecondorx_plot_y_max": {
+                    "type": "number",
+                    "default": 1,
+                    "description": "Upper log2ratio limit of additional WisecondorX plots (application-generated plots are unaffected)"
                 }
             }
         },

subworkflows/local/liquid_biopsy/main.nf

@@ -6,6 +6,7 @@ include { BAM_CNV_WISECONDORX          } from '../../../subworkflows/nf-core/bam
 include { ICHORCNA                     } from '../../../subworkflows/local/ichorcna/main'
 include { ASSEMBLE_WISECONDORX_OUTPUTS } from '../../../modules/local/assemble_wisecondorx_outputs/main'
 include { CONVERT_WISECONDORX_IMAGES   } from '../../../modules/local/convert_wisecondorx_images/main'
+include { PLOT_WISECONDORX_CNV         } from '../../../modules/local/plot_wisecondorx_cnv/main'
 
 workflow LIQUID_BIOPSY {
     take:
@@ -108,6 +109,12 @@ workflow LIQUID_BIOPSY {
         genome_plot = CONVERT_WISECONDORX_IMAGES.out.genome_plot
         // For compatibility with workflow output
         corrected_gistic_file = gistic_file
+
+       PLOT_WISECONDORX_CNV(CONVERT_GISTIC_SEG.out.segfile,
+                     BAM_CNV_WISECONDORX.out.bins_bed)
+        ch_versions = ch_versions.mix(PLOT_WISECONDORX_CNV.out.versions)
+
+
     }
     else {
         error("Uknown / unsupported analysis type ${caller}")