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annotate mykrobe_parser.R @ 5:deebc6410d13 draft

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planemo upload for repository https://github.com/phac-nml/mykrobe-parser commit bbf7dd6b56e8ee77cff1f98a42a5abadd681b7ac
author nml
date Thu, 09 May 2019 14:16:34 -0400
parents 8529045f0fdf
children 8e7e5a660942
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1 # Copyright Government of Canada 2018
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2 #
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3 # Written by: National Microbiology Laboratory, Public Health Agency of Canada
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4 #
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5 # Licensed under the Apache License, Version 2.0 (the "License"); you may not use
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6 # this work except in compliance with the License. You may obtain a copy of the
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7 # License at:
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8 #
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9 # http://www.apache.org/licenses/LICENSE-2.0
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10 #
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11 # Unless required by applicable law or agreed to in writing, software distributed
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12 # under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
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13 # CONDITIONS OF ANY KIND, either express or implied. See the License for the
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14 # specific language governing permissions and limitations under the License.
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17 # Parsing JSONs from Mykrobe Predict into CSV reports
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18 # Take the JSON output from Mykrobe, rearrange, output for LIMS
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19 # Adrian Zetner
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20 # August 2018
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22 # Libraries ####
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24 sink(stdout(), type = "message")
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26 suppressPackageStartupMessages({
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27 library(jsonlite)
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28 library(here)
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29 library(dplyr)
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30 library(purrr)
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31 library(tidyr)
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32 library(stringr)
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33 library(optparse)
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34 })
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36 # Define custom functions, variables, and paths. Collect and use CL arguments ####
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38 # Here's a function to recreate that output table from the input JSON files
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40 getResults <- function(listelement){
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41 # Define list levels for various elements of the json
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42 species <- names(listelement[[1]][["phylogenetics"]][["species"]])
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43 lineage <- names(listelement[[1]][["phylogenetics"]][["lineage"]])
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44 phylo_group <- names(listelement[[1]][["phylogenetics"]][["phylo_group"]])
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45 if("Non_tuberculosis_mycobacterium_complex" %in% phylo_group){
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46 warning(paste("Non-tuberculosis mycobacteria detected in file ", names(listelement), ". Skipping.", sep = ""))
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47 return()}
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48
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49 # Start building a list of all your various elements
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50 temp <- list(mykrobe_version = listelement[[1]][["version"]][["mykrobe-predictor"]],
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51 file = names(listelement), # One element
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52 plate_name = "test", # This probably needs changing
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53 sample = "sequence_calls", # Likewise change this
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54 phylo_group = phylo_group, # As above
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55 species = species, # As above
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56 lineage = lineage, # As above
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57 # The following expressions drill down into the list elements and pull out what is needed.
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58 # It's inelegant and vulnerable to changes in the input formats but if they're consistent it'll work
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59 phylo_group_per_covg = listelement[[1]][["phylogenetics"]][["phylo_group"]][[phylo_group]][["percent_coverage"]],
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60 species_per_covg = listelement[[1]][["phylogenetics"]][["species"]][[species]][["percent_coverage"]],
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61 lineage_per_covg = listelement[[1]][["phylogenetics"]][["lineage"]][[lineage]][["percent_coverage"]],
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62 phylo_group_depth = listelement[[1]][["phylogenetics"]][["phylo_group"]][[phylo_group]][["median_depth"]],
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63 species_depth = listelement[[1]][["phylogenetics"]][["species"]][[species]][["median_depth"]],
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64 lineage_depth = listelement[[1]][["phylogenetics"]][["lineage"]][[lineage]][["median_depth"]],
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65 Mykrobe_Resistance_probe_set = basename(listelement[[1]][["probe_sets"]][2]) # Is it always the second?
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66 )
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67
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68 # Super cool nested and vectorized (for SPEED!) functions to grab the predictions for drug sensitivity and gene variants
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69 # Both produce character vectors of the same length as the number of drugs tested in the same order
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70 # All of these also check if there are missing values in drug/susceptibility/variant elements and adds the column anyhow
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71
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72 if(length(map_chr(listelement[[1]][["susceptibility"]], "predict")) != 0){
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73 temp$susceptibility <- map_chr(listelement[[1]][["susceptibility"]], "predict")
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74 }else{
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75 temp$susceptibility <- NA
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76 }
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77
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78 if(length(names(listelement[[1]][["susceptibility"]])) != 0){
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79 temp$drug <- names(listelement[[1]][["susceptibility"]])
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80 }else{
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81 temp$drug <- NA
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82 }
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83
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84 mapped.variants <- map(listelement[[1]][["susceptibility"]], # Dig into the lists, pull out variants and collapse into chr vector
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85 ~ imap(.x[["called_by"]], # imap is shorthand for map2(x, names(x), ...), calling .y gets you the name / index of the current element
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86 ~ paste(.y,
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87 .x[["info"]][["coverage"]][["alternate"]][["median_depth"]],
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88 .x[["info"]][["coverage"]][["reference"]][["median_depth"]],
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89 .x[["info"]][["conf"]],
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90 sep = ":"))) %>%
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91 map_chr(~ paste(.x, collapse = "__"))
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92
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93 if(length(mapped.variants) != 0){
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94 temp$`variants (gene:alt_depth:wt_depth:conf)` <- mapped.variants
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95 }else{
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96 temp$`variants (gene:alt_depth:wt_depth:conf)` <- NA
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97 }
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98
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99 temp$`genes (prot_mut-ref_mut:percent_covg:depth)` <- NA
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100
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101 # Take that list and mash all the elements together as columns in a tibble, recycling as needed to fill in space
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102 # eg. phylo_group is repeated/recycled as many times as there are drugs tested
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103 as_tibble(temp)
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104 }
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105
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106 # Get command line arguments with optparse
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107 option_list = list(
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108 make_option(c("-f", "--file"),
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109 type="character",
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110 default=NULL,
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111 help='dataset file name or quoted comma separated names: eg. "file1,file2,file3"',
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112 metavar="character"),
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113 make_option(c("-d", "--dir"),
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114 type="character",
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115 default=NULL,
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116 help="directory location of json files",
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117 metavar="character"),
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118 make_option(c("-v", "--version"),
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119 type="character",
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120 default="",
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121 help="Mykrobe Workflow Version",
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122 metavar="character"),
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123 make_option(c("-D", "--depth"),
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124 type="integer",
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125 default=5,
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126 help="Minimum depth of coverage [default= %default]",
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127 metavar="integer"),
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128 make_option(c("-c", "--conf"),
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129 type="integer",
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130 default=10,
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131 help="Minimum genotype confidence for variant genotyping [default= %default]",
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132 metavar="integer"),
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133 make_option(c("-n", "--name"),
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134 type="character",
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135 default="",
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136 help="Name of the run",
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137 metavar="character")
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138 )
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139
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140 opt_parser = OptionParser(option_list=option_list)
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141 opt = parse_args(opt_parser)
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142
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143 if (is.null(opt$file) & is.null(opt$dir)){
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144 print_help(opt_parser)
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145 stop("At least one argument must be supplied to input file or directory", call.=FALSE)
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146 }
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147
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148 # Parameters to take from Galaxy/CL as args or however works best
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149 params <- c("", # Lims_Comment
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150 "", # Lims_INTComment
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151 opt$version, # Mykrobe_Workflow_Version
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152 opt$depth, # Mykrobe_min_depth_default_5
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153 opt$conf, # Mykrobe_min_conf_default_10
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154 "", # LIMS_file - empty as it's an upload field in LIMS
4
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155 opt$name) # Mutation_set_version
0
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156
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157 names(params) <- c("Lims_Comment",
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158 "Lims_INTComment",
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159 "Mykrobe_Workflow_Version",
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160 "Mykrobe_min_depth_default_5",
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161 "Mykrobe_min_conf_default_10",
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162 "LIMS_file",
4
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163 "Mutation_set_version")
0
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164
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165
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166 # A default report in the order our LIMS requires
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167
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168 # Make a default dataframe to combine the rest into and enforce column order / fill missing ones with NAs
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169 columns <- c("file",
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170 "Mykrobe_fabG1",
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171 "Mykrobe_katG",
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172 "Mykrobe_ahpC",
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173 "Mykrobe_inhA",
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174 "Mykrobe_ndh",
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175 "Isoniazid_R_mutations",
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176 "Isoniazid_Prediction",
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177 "Mykrobe_rpoB",
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178 "Rifampicin_R_mutations",
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179 "Rifampicin_Prediction",
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180 "Mykrobe_embB",
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181 "Mykrobe_embA",
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182 "Ethambutol_R_mutations",
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183 "Ethambutol_Prediction",
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184 "Mykrobe_pncA",
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185 "Mykrobe_rpsA",
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186 "Pyrazinamide_R_mutations",
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187 "Pyrazinamide_Prediction",
4
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188 "Mykrobe_Ofloxacin_gyrA",
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189 "Ofloxacin_R_mutations",
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190 "Ofloxacin_Prediction",
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191 "Mykrobe_Moxifloxacin_gyrA",
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192 "Moxifloxacin_R_mutations",
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193 "Moxifloxacin_Prediction",
0
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194 "Mykrobe_rpsL",
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195 "Mykrobe_Streptomycin_rrs",
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196 "Mykrobe_Streptomycin_gid",
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197 "Streptomycin_R_mutations",
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198 "Streptomycin_Prediction",
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199 "Mykrobe_Amikacin_rrs",
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200 "Amikacin_R_mutations",
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201 "Amikacin_Prediction",
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202 "Mykrobe_Capreomycin_rrs",
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203 "Mykrobe_Capreomycin_tlyA",
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204 "Capreomycin_R_mutations",
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205 "Capreomycin_Prediction",
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206 "Mykrobe_Kanamycin_rrs",
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207 "Mykrobe_Kanamycin_eis",
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208 "Kanamycin_R_mutations",
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209 "Kanamycin_Prediction",
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210 "Lims_Comment",
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211 "Lims_INTComment",
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212 "Mykrobe_Workflow_Version",
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213 "mykrobe_version",
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214 "Mykrobe_Resistance_probe_set",
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215 "Mykrobe_min_depth_default_5",
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216 "Mykrobe_min_conf_default_10",
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217 "LIMS_file",
4
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218 "Mutation_set_version")
0
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219
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220 report <- setNames(data.frame(matrix("", ncol = length(columns), nrow = 1), stringsAsFactors = F), columns)
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221
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222
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223 # List of drugs that are tested
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224 all_drugs <- c("Isoniazid",
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225 "Rifampicin",
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226 "Ethambutol",
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227 "Pyrazinamide",
4
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228 "Moxifloxacin",
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229 "Ofloxacin",
0
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230 "Streptomycin",
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231 "Amikacin",
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232 "Capreomycin",
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233 "Kanamycin")
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234
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235 # Do Stuff ####
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236
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237 # Import all the JSON files into a list of lists format ####
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238
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239 if (is.null(opt$file)){
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240 # opt$dir is used to get the list of files, a vector of non-duplicated files is then passed to map
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241 files <- list.files(path = opt$dir,
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242 pattern = "*.json",
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243 full.names = T)
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244 }else{
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245 files <- unlist(strsplit(opt$file, ","))
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246 }
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247
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248 files <- files[!duplicated(basename(files))]
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249
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250 list.of.json.files <- map(files,
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251 ~ fromJSON(.x, simplifyDataFrame = F)
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252 )
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253
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254
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255 # Apply that getResults function to each element in your list then bash it together into a final report
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256
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257 temp <- map(list.of.json.files, getResults) %>%
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258 bind_rows()
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259
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260
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261 # Predictions of resistance or susceptibility
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262 predictions.table <-
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263 temp %>%
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264 select(file, drug, susceptibility) %>%
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265 mutate(drug = paste(drug, "_Prediction", sep = "")) %>%
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266 spread(drug, susceptibility, fill = "failed") %>%
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267 select(-starts_with("NA"))
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268
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269 if (length(predictions.table) == 1){
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270 print(predictions.table)
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271 stop("No susceptibility results in files specified. Did the testing fail?", call.=FALSE)
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272 }
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273
2
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274 # Variants, if present
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275 if (0 < predictions.table %>%
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276 select(ends_with("_Prediction")) %>%
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277 unlist(use.names = F) %>%
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278 str_count("[R,r]") %>%
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279 sum()){
0
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280
2
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281 # Multiple resistance mutations and confidence per drug in the X_R_mutations column
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282 # Actual protein changes in Mykrobe_X columns
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283
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284 variants.temp <-
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285 temp %>%
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286 select(file, drug, variants = `variants (gene:alt_depth:wt_depth:conf)`) %>%
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287 mutate(variants = replace(variants, variants == "", NA)) %>% # Make missing data consistent...
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288 filter(!is.na(variants)) %>% # ...Then get rid of it
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289 mutate(tempcols = paste(drug, "R_mutations", sep = "_")) %>%
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290 mutate(R_mutations = variants) %>%
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291 mutate(variants = strsplit(variants, "__")) %>% # Split the mutations across rows (list first then split across rows)
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292 unnest(variants) %>%
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293 separate(variants, c("gene", "mutation"), "_") %>%
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294 mutate(columnname = ifelse(gene %in% c("gyrA", "tlyA", "rrs", "eis", "gid"), # Check for columns that include the drug name or not and paste accordingly
2
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295 paste("Mykrobe", drug, gene, sep = "_"),
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296 paste("Mykrobe", gene, sep = "_"))) %>%
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297 # Extract out the mutation information with a regex that covers all potential genes
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298 # This regex looks for whatever is ahead of the first colon and after the last hyphen
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299 mutate(mutation = str_match(mutation, "(.*)-.*:")[,2]) %>%
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300 select(file, tempcols, R_mutations, columnname, mutation)
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301
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302 # Split each kind of variants into its own temp table then merge
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303 variants.1 <-
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304 variants.temp %>%
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305 select(file, tempcols, R_mutations) %>%
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306 distinct() %>%
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307 spread(tempcols, R_mutations)
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308
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309 variants.2 <-
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310 variants.temp %>%
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311 select(file, columnname, mutation) %>%
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312 group_by(file, columnname) %>%
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313 summarise(mutation = paste(mutation, collapse = ";")) %>%
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314 spread(columnname, mutation)
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315
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316 variants.table <- full_join(variants.1, variants.2, by = "file")
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317 }else{
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318 variants.table <- data.frame(file=predictions.table$file, stringsAsFactors = F)
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319 }
0
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320
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321
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322 # Make a report ####
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323
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324 report <-
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325 temp %>%
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326 select(file, mykrobe_version, Mykrobe_Resistance_probe_set) %>% # Get important info from initial table
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327 distinct() %>% # Drop duped rows and combine all the tables together
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328 full_join(variants.table) %>%
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329 full_join(predictions.table) %>%
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330 bind_rows(report) %>% # Use bind_rows to add columns (eg. unteseted drugs) to the final output
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331 filter(file != "")
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332
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333 # Only add the 'no mutation' replacement to the columns that actually have a result
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334 report <-
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335 report %>%
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336 filter_at(vars(ends_with("_Prediction")), any_vars(. != "failed")) %>%
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337 mutate_at(vars(starts_with("Mykrobe_")), funs(replace(., is.na(.), "No Mutation"))) %>%
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338 full_join(anti_join(report, ., by = "file")) %>%
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339 select(columns)
0
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340
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341
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342 # Add in the parameters fed from Galaxy using named character vector
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343 report <-
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344 report %>%
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345 mutate(
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346 Lims_Comment = params["Lims_Comment"],
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347 Lims_INTComment = params["Lims_INTComment"],
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348 Mykrobe_Workflow_Version = params["Mykrobe_Workflow_Version"],
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349 Mykrobe_min_depth_default_5 = params["Mykrobe_min_depth_default_5"],
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350 Mykrobe_min_conf_default_10 = params["Mykrobe_min_conf_default_10"],
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351 LIMS_file = params["LIMS_file"],
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352 Mutation_set_version = params["Mutation_set_version"]
0
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353 )
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354
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355
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356 #View(report)
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357
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358 # Write some output
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359 # Report as is
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360 write.csv(report, "output-report.csv", row.names = F)
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361 print("Writing Susceptibility report to CSV as output-report.csv")
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362
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363 # Select specific columns from temp and output them
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364 temp %>%
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365 select(file,
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366 phylo_group,
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367 species,
6eae14751768 planemo upload for repository https://github.com/phac-nml/mykrobe-parser commit 0b64469b5d819a9c5b9ea85d07ccbc3b5fb6b25e-dirty
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368 lineage,
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369 phylo_group_per_covg,
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370 species_per_covg,
6eae14751768 planemo upload for repository https://github.com/phac-nml/mykrobe-parser commit 0b64469b5d819a9c5b9ea85d07ccbc3b5fb6b25e-dirty
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371 lineage_per_covg,
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372 phylo_group_depth,
6eae14751768 planemo upload for repository https://github.com/phac-nml/mykrobe-parser commit 0b64469b5d819a9c5b9ea85d07ccbc3b5fb6b25e-dirty
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373 species_depth,
6eae14751768 planemo upload for repository https://github.com/phac-nml/mykrobe-parser commit 0b64469b5d819a9c5b9ea85d07ccbc3b5fb6b25e-dirty
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374 lineage_depth) %>%
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375 distinct() %>%
6eae14751768 planemo upload for repository https://github.com/phac-nml/mykrobe-parser commit 0b64469b5d819a9c5b9ea85d07ccbc3b5fb6b25e-dirty
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376 write.csv("output-jsondata.csv", row.names = F)
2
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377 print("Writing JSON data to CSV as output-jsondata.csv")
0
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378 sink(NULL, type="message") # close the sink
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379
4
8529045f0fdf planemo upload for repository https://github.com/phac-nml/mykrobe-parser commit 34d9c47b9451e5f7843028dba22b96d125fb09f5
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380 quit()