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annotate scpipe.R @ 2:5c4bca9dd4a2 draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scpipe commit 60e2a9e9129a22924c55b11b218b39d913c7e686
author iuc
date Mon, 14 Jan 2019 08:06:47 -0500
parents 32e1bfc6b7b2
children 7397e6badc11
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32e1bfc6b7b2 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scpipe commit 8908da9cdd112ae0943dbf1eccb221e84cd99ca7
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1 options( show.error.messages=F, error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
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2
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3 # we need that to not crash galaxy with an UTF8 error on German LC settings.
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4 loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
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5
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6 suppressPackageStartupMessages({
32e1bfc6b7b2 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scpipe commit 8908da9cdd112ae0943dbf1eccb221e84cd99ca7
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7 library(scPipe)
32e1bfc6b7b2 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scpipe commit 8908da9cdd112ae0943dbf1eccb221e84cd99ca7
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8 library(SingleCellExperiment)
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9 library(optparse)
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10 library(readr)
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11 library(ggplot2)
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12 library(plotly)
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13 library(DT)
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14 library(scater)
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15 library(scran)
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16 library(scales)
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17 library(Rtsne)
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18 })
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19
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20 option_list <- list(
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21 make_option(c("-bam","--bam"), type="character", help="BAM file"),
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22 make_option(c("-fasta","--fasta"), type="character", help="Genome fasta file"),
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23 make_option(c("-exons","--exons"), type="character", help="Exon annotation gff3 file"),
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24 make_option(c("-organism","--organism"), type="character", help="Organism e.g. hsapiens_gene_ensembl"),
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25 make_option(c("-barcodes","--barcodes"), type="character", help="Cell barcodes csv file"),
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26 make_option(c("-read1","--read1"), type="character", help="Read 1 fastq.gz"),
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27 make_option(c("-read2","--read2"), type="character", help="Read 2 fastq.gz"),
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28 make_option(c("-samplename","--samplename"), type="character", help="Name to use for sample"),
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29 make_option(c("-bs1","--bs1"), type="integer", help="Barcode start in Read 1"),
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30 make_option(c("-bl1","--bl1"), type="integer", help="Barcode length in Read 1"),
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31 make_option(c("-bs2","--bs2"), type="integer", help="Barcode start in Read 2"),
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32 make_option(c("-bl2","--bl2"), type="integer", help="Barcode length in Read 2"),
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33 make_option(c("-us","--us"), type="integer", help="UMI start in Read 2"),
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34 make_option(c("-ul","--ul"), type="integer", help="UMI length in Read 2"),
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35 make_option(c("-rmlow","--rmlow"), type="logical", help="Remove reads with N in barcode or UMI"),
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36 make_option(c("-rmN","--rmN"), type="logical", help="Remove reads with low quality"),
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37 make_option(c("-minq","--minq"), type="integer", help="Minimum read quality"),
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38 make_option(c("-numbq","--numbq"), type="integer", help="Maximum number of bases below minq"),
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39 make_option(c("-stnd","--stnd"), type="logical", help="Perform strand-specific mapping"),
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40 make_option(c("-max_mis","--max_mis"), type="integer", help="Maximum mismatch allowed in barcode"),
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41 make_option(c("-UMI_cor","--UMI_cor"), type="integer", help="Correct UMI sequence error"),
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42 make_option(c("-gene_fl","--gene_fl"), type="logical", help="Remove low abundant genes"),
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43 make_option(c("-max_reads","--max_reads"), type="integer", help="Maximum reads processed"),
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44 make_option(c("-min_count","--min_count"), type="integer", help="Minimum count to keep"),
2
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45 make_option(c("-metrics_matrix","--metrics_matrix"), type="logical", help="QC metrics matrix"),
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46 make_option(c("-keep_outliers","--keep_outliers"), type="logical", help="Keep outlier cells"),
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47 make_option(c("-report","--report"), type="logical", help="HTML report of plots"),
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48 make_option(c("-rdata","--rdata"), type="logical", help="Output RData file"),
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49 make_option(c("-nthreads","--nthreads"), type="integer", help="Number of threads")
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50 )
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51
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52 parser <- OptionParser(usage = "%prog [options] file", option_list=option_list)
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53 args = parse_args(parser)
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54
2
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55 bam = args$bam
0
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56 fa_fn = args$fasta
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57 anno_fn = args$exons
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58 fq_R1 = args$read1
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59 fq_R2 = args$read2
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60 read_structure = list(
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61 bs1 = args$bs1, # barcode start position in fq_R1, -1 indicates no barcode
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62 bl1 = args$bl1, # barcode length in fq_R1, 0 since no barcode present
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63 bs2 = args$bs2, # barcode start position in fq_R2
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64 bl2 = args$bl2, # barcode length in fq_R2
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65 us = args$us, # UMI start position in fq_R2
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66 ul = args$ul # UMI length
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67 )
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68
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69 if (args$us == -1) {
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70 has_umi = FALSE
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71 } else {
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72 has_umi = TRUE
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73 }
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74
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75 filter_settings=list(rmlow=args$rmlow, rmN=args$rmN, minq=args$minq, numbq=args$numbq)
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76
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77 # Outputs
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78 out_dir = "."
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79 mapped_bam = file.path(out_dir, "aligned.mapped.bam")
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80
2
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81 # if input is fastqs
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82 if (!is.null(fa_fn)) {
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83 fasta_index = file.path(out_dir, paste0(fa_fn, ".fasta_index"))
5c4bca9dd4a2 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scpipe commit 60e2a9e9129a22924c55b11b218b39d913c7e686
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84 combined_fastq = file.path(out_dir, "combined.fastq")
5c4bca9dd4a2 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scpipe commit 60e2a9e9129a22924c55b11b218b39d913c7e686
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85 aligned_bam = file.path(out_dir, "aligned.bam")
0
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86
2
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87 print("Trimming barcodes")
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88 sc_trim_barcode(combined_fastq,
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89 fq_R1,
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90 fq_R2,
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91 read_structure=read_structure,
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92 filter_settings=filter_settings)
0
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93
2
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94 print("Building genome index")
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95 Rsubread::buildindex(basename=fasta_index, reference=fa_fn)
0
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96
2
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97 print("Aligning reads to genome")
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98 Rsubread::align(index=fasta_index,
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99 readfile1=combined_fastq,
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100 output_file=aligned_bam,
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101 nthreads=args$nthreads)
0
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102
2
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103 if (!is.null(args$barcodes)) {
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104 barcode_anno=args$barcodes
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105 } else {
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106 print("Detecting barcodes")
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107 # detect 10X barcodes and generate sample_index.csv file
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108 barcode_anno = "sample_index.csv"
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109 sc_detect_bc(
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110 infq=combined_fastq,
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111 outcsv=barcode_anno,
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112 bc_len=read_structure$bl2,
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113 max_reads=args$max_reads,
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114 min_count=args$min_count,
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115 max_mismatch=args$max_mis
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116 )
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117 }
0
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118 } else {
2
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119 aligned_bam = file.path(out_dir, bam)
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120 barcode_anno=args$barcodes
0
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121 }
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122
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123 print("Assigning reads to exons")
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124 sc_exon_mapping(aligned_bam, mapped_bam, anno_fn, bc_len=read_structure$bl2, UMI_len=read_structure$ul, stnd=args$stnd)
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125
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126 print("De-multiplexing data")
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127 sc_demultiplex(mapped_bam, out_dir, barcode_anno, has_UMI=has_umi)
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128
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129 print("Counting genes")
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130 sc_gene_counting(out_dir, barcode_anno, UMI_cor=args$UMI_cor, gene_fl=args$gene_fl)
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131
2
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132 print("Performing QC")
0
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133 sce <- create_sce_by_dir(out_dir)
2
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134 pdf("plots.pdf")
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135 plot_demultiplex(sce)
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136 if (has_umi) {
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137 p = plot_UMI_dup(sce)
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138 print(p)
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139 }
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140 sce = calculate_QC_metrics(sce)
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141 sce = detect_outlier(sce)
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142 p = plot_mapping(sce, percentage=TRUE, dataname=args$samplename)
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143 print(p)
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144 p = plot_QC_pairs(sce)
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145 print(p)
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146 dev.off()
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147
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148 print("Removing outliers")
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149 if (is.null(args$keep_outliers)) {
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150 sce = remove_outliers(sce)
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151 gene_counts <- counts(sce)
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152 write.table(data.frame("gene_id"=rownames(gene_counts), gene_counts), file="gene_count.tsv", sep="\t", quote=FALSE, row.names=FALSE)
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153 }
0
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154
2
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155 if (!is.null(args$metrics_matrix)) {
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156 metrics <- colData(sce, internal=TRUE)
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157 write.table(data.frame("cell_id"=rownames(metrics), metrics), file="metrics_matrix.tsv", sep="\t", quote=FALSE, row.names=FALSE)
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158 }
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159
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160 if (!is.null(args$report) & (!is.null(fa_fn))) {
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161 print("Creating report")
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162 create_report(sample_name=args$samplename,
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163 outdir=out_dir,
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164 r1=fq_R1,
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165 r2=fq_R2,
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166 outfq=combined_fastq,
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167 read_structure=read_structure,
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168 filter_settings=filter_settings,
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169 align_bam=aligned_bam,
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170 genome_index=fasta_index,
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171 map_bam=mapped_bam,
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172 exon_anno=anno_fn,
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173 stnd=args$stnd,
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174 fix_chr=FALSE,
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175 barcode_anno=barcode_anno,
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176 max_mis=args$max_mis,
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177 UMI_cor=args$UMI_cor,
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178 gene_fl=args$gene_fl,
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179 organism=args$organism,
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180 gene_id_type="ensembl_gene_id")
0
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181 }
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182
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183 if (!is.null(args$rdata) ) {
2
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184 save(sce, file = file.path(out_dir,"scPipe_analysis.RData"))
0
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185 }
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186
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187 sessionInfo()