annotate scpipe.R @ 5:a3b3ec00bf8f draft default tip

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scpipe commit fdf7345541065bceabb72dda6a4ce62967cca2e8"
author iuc
date Fri, 26 Feb 2021 22:26:37 +0000
parents 7397e6badc11
children
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1 err_foo <- function() {
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2 cat(geterrmessage(), file = stderr());
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3 q("no", 1, F)
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4 }
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5 options(show.error.messages = F, error = err_foo)
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6
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7 # we need that to not crash galaxy with an UTF8 error on German LC settings.
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8 loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
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9
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10 suppressPackageStartupMessages({
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11 library(scPipe)
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12 library(SingleCellExperiment)
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13 library(optparse)
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14 library(readr)
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15 library(ggplot2)
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16 library(plotly)
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17 library(DT)
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18 library(scater)
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19 library(scran)
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20 library(scales)
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21 library(Rtsne)
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22 })
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23
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24 option_list <- list(
3
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25 make_option(c("-bam", "--bam"), type = "character", help = "BAM file"),
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26 make_option(c("-fasta", "--fasta"), type = "character", help = "Genome fasta file"),
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27 make_option(c("-exons", "--exons"), type = "character", help = "Exon annotation gff3 file"),
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28 make_option(c("-organism", "--organism"), type = "character", help = "Organism e.g. hsapiens_gene_ensembl"),
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29 make_option(c("-barcodes", "--barcodes"), type = "character", help = "Cell barcodes csv file"),
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30 make_option(c("-read1", "--read1"), type = "character", help = "Read 1 fastq.gz"),
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31 make_option(c("-read2", "--read2"), type = "character", help = "Read 2 fastq.gz"),
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32 make_option(c("-samplename", "--samplename"), type = "character", help = "Name to use for sample"),
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33 make_option(c("-bs1", "--bs1"), type = "integer", help = "Barcode start in Read 1"),
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34 make_option(c("-bl1", "--bl1"), type = "integer", help = "Barcode length in Read 1"),
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35 make_option(c("-bs2", "--bs2"), type = "integer", help = "Barcode start in Read 2"),
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36 make_option(c("-bl2", "--bl2"), type = "integer", help = "Barcode length in Read 2"),
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37 make_option(c("-us", "--us"), type = "integer", help = "UMI start in Read 2"),
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38 make_option(c("-ul", "--ul"), type = "integer", help = "UMI length in Read 2"),
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39 make_option(c("-rmlow", "--rmlow"), type = "logical", help = "Remove reads with N in barcode or UMI"),
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40 make_option(c("-rmN", "--rmN"), type = "logical", help = "Remove reads with low quality"),
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41 make_option(c("-minq", "--minq"), type = "integer", help = "Minimum read quality"),
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42 make_option(c("-numbq", "--numbq"), type = "integer", help = "Maximum number of bases below minq"),
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43 make_option(c("-stnd", "--stnd"), type = "logical", help = "Perform strand-specific mapping"),
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44 make_option(c("-max_mis", "--max_mis"), type = "integer", help = "Maximum mismatch allowed in barcode"),
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45 make_option(c("-UMI_cor", "--UMI_cor"), type = "integer", help = "Correct UMI sequence error"),
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46 make_option(c("-gene_fl", "--gene_fl"), type = "logical", help = "Remove low abundant genes"),
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47 make_option(c("-max_reads", "--max_reads"), type = "integer", help = "Maximum reads processed"),
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48 make_option(c("-min_count", "--min_count"), type = "integer", help = "Minimum count to keep"),
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49 make_option(c("-metrics_matrix", "--metrics_matrix"), type = "logical", help = "QC metrics matrix"),
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50 make_option(c("-keep_outliers", "--keep_outliers"), type = "logical", help = "Keep outlier cells"),
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51 make_option(c("-report", "--report"), type = "logical", help = "HTML report of plots"),
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52 make_option(c("-rdata", "--rdata"), type = "logical", help = "Output RData file"),
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53 make_option(c("-nthreads", "--nthreads"), type = "integer", help = "Number of threads")
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54 )
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55
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56 parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
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57 args <- parse_args(parser)
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59 bam <- args$bam
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60 fa_fn <- args$fasta
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61 anno_fn <- args$exons
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62 fq_r1 <- args$read1
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63 fq_r2 <- args$read2
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64 read_structure <- list(bs1 = args$bs1, # barcode start position in fq_r1, -1 indicates no barcode
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65 bl1 = args$bl1, # barcode length in fq_r1, 0 since no barcode present
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66 bs2 = args$bs2, # barcode start position in fq_r2
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67 bl2 = args$bl2, # barcode length in fq_r2
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68 us = args$us, # UMI start position in fq_r2
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69 ul = args$ul # UMI length
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70 )
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71
0
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72 if (args$us == -1) {
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73 has_umi <- FALSE
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74 } else {
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75 has_umi <- TRUE
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76 }
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77
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78 filter_settings <- list(rmlow = args$rmlow,
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79 rmN = args$rmN,
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80 minq = args$minq,
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81 numbq = args$numbq)
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83 # Outputs
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84 out_dir <- "."
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85 mapped_bam <- file.path(out_dir, "aligned.mapped.bam")
0
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86
2
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87 # if input is fastqs
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88 if (!is.null(fa_fn)) {
3
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89 fasta_index <- file.path(out_dir, paste0(fa_fn, ".fasta_index"))
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90 combined_fastq <- file.path(out_dir, "combined.fastq")
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91 aligned_bam <- file.path(out_dir, "aligned.bam")
0
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92
2
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93 print("Trimming barcodes")
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94 sc_trim_barcode(combined_fastq,
3
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95 fq_r1,
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96 fq_r2,
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97 read_structure = read_structure,
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98 filter_settings = filter_settings)
0
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99
2
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100 print("Building genome index")
3
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101 Rsubread::buildindex(basename = fasta_index, reference = fa_fn)
0
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102
2
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103 print("Aligning reads to genome")
3
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104 Rsubread::align(index = fasta_index,
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105 readfile1 = combined_fastq,
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106 output_file = aligned_bam,
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107 nthreads = args$nthreads)
0
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108
2
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109 if (!is.null(args$barcodes)) {
3
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110 barcode_anno <- args$barcodes
2
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111 } else {
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112 print("Detecting barcodes")
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113 # detect 10X barcodes and generate sample_index.csv file
3
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114 barcode_anno <- "sample_index.csv"
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115 sc_detect_bc(infq = combined_fastq,
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116 outcsv = barcode_anno,
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117 bc_len = read_structure$bl2,
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118 max_reads = args$max_reads,
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119 min_count = args$min_count,
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120 max_mismatch = args$max_mis
2
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121 )
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122 }
0
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123 } else {
3
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124 aligned_bam <- file.path(out_dir, bam)
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125 barcode_anno <- args$barcodes
0
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126 }
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127
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128 print("Assigning reads to exons")
3
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129 sc_exon_mapping(aligned_bam, mapped_bam, anno_fn, bc_len = read_structure$bl2, UMI_len = read_structure$ul, stnd = args$stnd)
0
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130
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131 print("De-multiplexing data")
3
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132 sc_demultiplex(mapped_bam, out_dir, barcode_anno, has_UMI = has_umi)
0
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133
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134 print("Counting genes")
3
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135 sc_gene_counting(out_dir, barcode_anno, UMI_cor = args$UMI_cor, gene_fl = args$gene_fl)
0
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136
2
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137 print("Performing QC")
0
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138 sce <- create_sce_by_dir(out_dir)
2
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139 pdf("plots.pdf")
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140 plot_demultiplex(sce)
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141 if (has_umi) {
3
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142 p <- plot_UMI_dup(sce)
2
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143 print(p)
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144 }
3
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145 sce <- calculate_QC_metrics(sce)
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146 sce <- detect_outlier(sce)
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147 p <- plot_mapping(sce, percentage = TRUE, dataname = args$samplename)
2
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148 print(p)
3
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149 p <- plot_QC_pairs(sce)
2
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150 print(p)
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151 dev.off()
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152
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153 print("Removing outliers")
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154 if (is.null(args$keep_outliers)) {
3
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155 sce <- remove_outliers(sce)
2
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156 gene_counts <- counts(sce)
3
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157 write.table(data.frame("gene_id" = rownames(gene_counts), gene_counts), file = "gene_count.tsv", sep = "\t", quote = FALSE, row.names = FALSE)
2
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158 }
0
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159
2
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160 if (!is.null(args$metrics_matrix)) {
3
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161 metrics <- colData(sce, internal = TRUE)
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162 write.table(data.frame("cell_id" = rownames(metrics), metrics), file = "metrics_matrix.tsv", sep = "\t", quote = FALSE, row.names = FALSE)
2
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163 }
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164
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165 if (!is.null(args$report) & (!is.null(fa_fn))) {
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166 print("Creating report")
3
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167 create_report(sample_name = args$samplename,
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168 outdir = out_dir,
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169 r1 = fq_r1,
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170 r2 = fq_r2,
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171 outfq = combined_fastq,
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172 read_structure = read_structure,
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173 filter_settings = filter_settings,
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174 align_bam = aligned_bam,
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175 genome_index = fasta_index,
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176 map_bam = mapped_bam,
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177 exon_anno = anno_fn,
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178 stnd = args$stnd,
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179 fix_chr = FALSE,
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180 barcode_anno = barcode_anno,
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181 max_mis = args$max_mis,
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182 UMI_cor = args$UMI_cor,
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183 gene_fl = args$gene_fl,
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184 organism = args$organism,
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185 gene_id_type = "ensembl_gene_id")
0
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186 }
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187
3
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188 if (!is.null(args$rdata)) {
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189 save(sce, file = file.path(out_dir, "scPipe_analysis.RData"))
0
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190 }
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191
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192 sessionInfo()