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annotate facets_analysis.R @ 2:66a56502199d draft

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planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/facets commit 0176d2cc4f1caf0ab948ef72efb25ccce735461e
author artbio
date Fri, 03 Oct 2025 23:59:36 +0000
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66a56502199d planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/facets commit 0176d2cc4f1caf0ab948ef72efb25ccce735461e
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1 #!/usr/bin/env Rscript
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3 # Description:
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4 # This script serves as the backend for the Galaxy FACETS Analysis tool.
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5 # It takes a SNP pileup file as input and performs allele-specific copy
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6 # number analysis using the R package 'facets'.
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7 # ==============================================================================
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9 # --- 1. Load Libraries ---
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10 suppressPackageStartupMessages(library(argparse))
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11 suppressPackageStartupMessages(library(facets))
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13 # --- 2. Define and Parse Arguments ---
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15 # Create the parser
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16 parser <- ArgumentParser(description = "Run FACETS algorithm on a SNP pileup file.")
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18 # Define arguments
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19 parser$add_argument("--pileup",
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20 type = "character", required = TRUE,
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21 help = "Path to the gzipped pileup CSV file."
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22 )
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23 parser$add_argument("--sample_id",
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24 type = "character", required = TRUE,
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25 help = "Sample ID used for plot titles and metadata."
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26 )
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28 parser$add_argument("--output_seg",
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29 type = "character", required = TRUE,
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30 help = "Path for the output segmentation file (TSV)."
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31 )
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32 parser$add_argument("--output_summary",
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33 type = "character", required = TRUE,
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34 help = "Path for the output summary file (TSV)."
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35 )
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36 parser$add_argument("--output_plots",
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37 type = "character", required = TRUE,
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38 help = "Path for the output plots file (PDF)."
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39 )
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41 parser$add_argument("--cval",
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42 type = "double", default = 150,
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43 help = "Critical value for segmentation."
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44 )
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45 parser$add_argument("--min_nhet",
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46 type = "integer", default = 25,
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47 help = "Minimum number of heterozygous SNPs per segment."
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48 )
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49 parser$add_argument("--snp_nbhd",
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50 type = "integer", default = 300,
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51 help = "SNP neighborhood size for pre-processing. Crucial for sparse VCFs."
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52 )
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53 parser$add_argument("--gbuild",
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54 type = "character", default = "hg38",
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55 choices = c("hg19", "hg38", "hg18", "mm9", "mm10"),
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56 help = "Genome build used for alignment."
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57 )
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59 # --- 3. Main Analysis Function ---
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60 main <- function(args) {
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61 # Set seed for reproducibility
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62 set.seed(1965)
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64 # --- Read the data with readSnpMatrix() from facets ---
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65 rcmat <- readSnpMatrix(args$pileup)
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67 # --- Pre-process sample ---
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68 xx <- preProcSample(rcmat, gbuild = args$gbuild, snp.nbhd = args$snp_nbhd)
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70 # --- Process sample (segmentation) ---
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71 oo <- procSample(xx, cval = args$cval, min.nhet = args$min_nhet)
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73 # --- Estimate ploidy/purity ---
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74 fit <- emcncf(oo)
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76 # Write the main segmentation file
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77 cncf_output <- fit$cncf
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78 if (nrow(cncf_output) > 0) {
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79 cncf_output$purity <- fit$purity
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80 cncf_output$ploidy <- fit$ploidy
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81 # Reorder columns to have purity/ploidy first for clarity
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82 cncf_output <- cncf_output[, c("purity", "ploidy", setdiff(names(cncf_output), c("purity", "ploidy")))]
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83 }
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84 write.table(cncf_output, file = args$output_seg, sep = "\t", quote = FALSE, row.names = FALSE)
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85
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86 # Write a key-value summary file
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87 # A NULL value is replaced by NA to preserve vector length.
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88 summary_df <- data.frame(
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89 Parameter = c(
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90 "sample_id", "purity", "ploidy", "dipLogR", "loglik",
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91 "cval_param", "min_nhet_param", "snp_nbhd_param", "gbuild_param"
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92 ),
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93 Value = c(
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94 args$sample_id,
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95 ifelse(is.null(fit$purity), NA, fit$purity),
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96 ifelse(is.null(fit$ploidy), NA, fit$ploidy),
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97 ifelse(is.null(fit$dipLogR), NA, fit$dipLogR),
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98 ifelse(is.null(fit$loglik), NA, fit$loglik),
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99 args$cval,
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100 args$min_nhet,
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101 args$snp_nbhd,
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102 args$gbuild
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103 )
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104 )
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105 write.table(summary_df, file = args$output_summary, sep = "\t", quote = FALSE, row.names = FALSE)
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106
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107 # Generate the plots PDF
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108 pdf(file = args$output_plots, width = 12, height = 8)
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109 plotSample(x = oo, emfit = fit, sname = args$sample_id)
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110 dev.off()
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111 }
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112
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113 # --- 4. Execution Block ---
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114 if (!interactive()) {
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115 args <- parser$parse_args()
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116 main(args)
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117 }