Mercurial > repos > tomnl > assess_purity_msms

annotate create_sqlite_db.R @ 20:6c8c4452b8ea draft

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planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit 04023134d8f28e85927ca293373c506484149ead-dirty
author tomnl
date Thu, 31 May 2018 09:08:55 -0400
parents 5ca214b3423e
children f428f3fb82ad
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1 library(msPurity)
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2 library(optparse)
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3 library(xcms)
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4 library(CAMERA)
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5 print(sessionInfo())
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6 print('CREATING DATABASE')
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9 xset_pa_filename_fix <- function(opt, pa, xset){
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12 if (!is.null(opt$mzML_files) && !is.null(opt$galaxy_names)){
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13 # NOTE: Relies on the pa@fileList having the names of files given as 'names' of the variables
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14 # needs to be done due to Galaxy moving the files around and screwing up any links to files
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16 filepaths <- trimws(strsplit(opt$mzML_files, ',')[[1]])
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17 filepaths <- filepaths[filepaths != ""]
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18 new_names <- basename(filepaths)
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20 galaxy_names <- trimws(strsplit(opt$galaxy_names, ',')[[1]])
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21 galaxy_names <- galaxy_names[galaxy_names != ""]
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23 nsave <- names(pa@fileList)
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24 old_filenames <- basename(pa@fileList)
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25 pa@fileList <- filepaths[match(names(pa@fileList), galaxy_names)]
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26 names(pa@fileList) <- nsave
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28 pa@puritydf$filename <- basename(pa@fileList[match(pa@puritydf$filename, old_filenames)])
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29 pa@grped_df$filename <- basename(pa@fileList[match(pa@grped_df$filename, old_filenames)])
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30 }
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33 if(!all(basename(pa@fileList)==basename(xset@filepaths))){
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34 if(!all(names(pa@fileList)==basename(xset@filepaths))){
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35 print('FILELISTS DO NOT MATCH')
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36 message('FILELISTS DO NOT MATCH')
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37 quit(status = 1)
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38 }else{
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39 xset@filepaths <- unname(pa@fileList)
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40 }
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41 }
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44 return(list(pa, xset))
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45 }
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50 option_list <- list(
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51 make_option(c("-o", "--out_dir"), type="character"),
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52 make_option("--pa", type="character"),
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53 make_option("--xset_xa", type="character"),
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54 make_option("--xcms_camera_option", type="character"),
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55 make_option("--eic", action="store_true"),
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56 make_option("--cores", default=4),
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57 make_option("--mzML_files", type="character"),
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58 make_option("--galaxy_names", type="character"),
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59 make_option("--grp_peaklist", type="character"),
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60 make_option("--db_name", type="character", default='lcms_data.sqlite'),
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61 make_option("--raw_rt_columns", action="store_true"),
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62 make_option("--metfrag_result", type="character"),
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63 make_option("--sirius_csifingerid_result", type="character"),
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64 make_option("--probmetab_result", type="character")
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65 )
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68 # store options
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69 opt<- parse_args(OptionParser(option_list=option_list))
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71 loadRData <- function(rdata_path, name){
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72 #loads an RData file, and returns the named xset object if it is there
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73 load(rdata_path)
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74 return(get(ls()[ls() == name]))
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75 }
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77 print(paste('pa', opt$pa))
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78 print(opt$xset)
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79 print(opt$xcms_camera_option)
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80 # Requires
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81 pa <- loadRData(opt$pa, 'pa')
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84 print(pa@fileList)
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87 if (opt$xcms_camera_option=='xcms'){
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88 xset <- loadRData(opt$xset, 'xset')
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89 fix <- xset_pa_filename_fix(opt, pa, xset)
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90 pa <- fix[[1]]
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91 xset <- fix[[2]]
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92 xa <- NULL
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93 }else{
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95 xa <- loadRData(opt$xset, 'xa')
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96 fix <- xset_pa_filename_fix(opt, pa, xa@xcmsSet)
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97 pa <- fix[[1]]
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98 xa@xcmsSet <- fix[[2]]
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99 xset <- NULL
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100 }
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101
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102
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103
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104
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105
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106 if(is.null(opt$grp_peaklist)){
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107 grp_peaklist = NA
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108 }else{
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109 grp_peaklist = opt$grp_peaklist
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110 }
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111
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112
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113
1
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114
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115
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116 db_pth <- msPurity::create_database(pa, xset=xset, xsa=xa, out_dir=opt$out_dir,
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117 grp_peaklist=grp_peaklist, db_name=opt$db_name)
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118
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119 print(db_pth)
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120
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121 if (!is.null(opt$eic)){
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122 if (is.null(opt$raw_rt_columns)){
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123 rtrawColumns <- FALSE
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124 }else{
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125 rtrawColumns <- TRUE
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126 }
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127 if (is.null(xset)){
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128 xset <- xa@xcmsSet
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129 }
14
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130 # previous check should have matched filelists together
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131 xset@filepaths <- unname(pa@fileList)
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132
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133 # Saves the EICS into the previously created database
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134 px <- msPurity::purityX(xset, saveEIC = TRUE,
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135 cores=1, sqlitePth=db_pth,
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136 rtrawColumns = rtrawColumns)
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137 }
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138
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139 con <- DBI::dbConnect(RSQLite::SQLite(), db_pth)
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140
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141 add_extra_table_elucidation <- function(name, pth, db_con, filter_Score=NA, filter_Rank=NA){
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142 if (is.null(pth)){
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143 return(0)
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144 }
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145 index <- 0
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146 chunkSize <- 5000
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147 print(pth)
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148 con <- file(description=pth,open="r")
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149 df <- read.table(con, nrows=chunkSize, header = TRUE, sep='\t', stringsAsFactors = FALSE, comment.char = "")
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150 headers = colnames(df)
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151 print(head(df))
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152 write_to_table(df, db_con, name, FALSE, filter_Score, filter_Rank)
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153
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154 repeat {
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155 index <- index + 1
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156 print(paste('Processing rows:', index * chunkSize))
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157
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158 if (nrow(df) != chunkSize){
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159 print('Processed all files!')
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160 break
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161 }
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162
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163 df <- read.table(con, nrows=chunkSize, skip=0, header = FALSE, sep='\t', stringsAsFactors = FALSE, comment.char = "")
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164 colnames(df) <- headers
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165
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166
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167 write_to_table(df, db_con, name, TRUE, filter_Score, filter_Rank)
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168
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169
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170 break
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171 }
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172 close(con)
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173
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174 }
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175
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176 write_to_table <- function(df, db_con, name, append, filter_Score, filter_Rank){
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177
20
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178 df <- df[!df$UID=='UID',]
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179 print(filter_Score)
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180 print(filter_Rank)
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181 print('filter rank and score')
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182
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183 if (!is.na(filter_Score)){
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184 df <- df[df$Score>=filter_Score,]
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185 }
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186
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187 if (!is.na(filter_Rank)){
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188
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189 df <- df[df$Rank<=filter_Rank,]
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190 }
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191
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192 # get peakid, an scan id
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193 df_ids <- stringr::str_split_fixed(df$UID, '-', 3)
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194 colnames(df_ids) <- c('grp_id', 'file_id', 'pid')
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195 df <- cbind(df_ids, df)
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196 DBI::dbWriteTable(db_con, name=name, value=df, row.names=FALSE, append=append)
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197 }
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198
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199 add_probmetab <- function(pth, con){
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200 if (!is.null(pth)){
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201
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202 df <- read.table(pth, header = TRUE, sep='\t', stringsAsFactors = FALSE, comment.char = "")
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203 df$grp_id <- 1:nrow(df)
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204 start <- T
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205 for (i in 1:nrow(df)){
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206
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207 x <- df[i,]
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208
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209
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210 if(is.na(x$proba) | x$proba =='NA'){
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211
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212 next
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213 }
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214
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215 mpc <- stringr::str_split(x$mpc, ';')
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216 proba <- stringr::str_split(x$proba, ';')
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217
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218 for (j in 1:length(mpc[[1]])){
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219
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220 row <- c(x$grp_id, x$propmz, mpc[[1]][j], proba[[1]][j])
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221
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222 if (start){
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223 df_out <- data.frame(t(row), stringsAsFactors=F)
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224 start <- F
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225 }else{
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226 df_out <- data.frame(rbind(df_out, row), stringsAsFactors=F)
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227 }
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228 print(df_out)
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229
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230 }
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231
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232 }
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233
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234 colnames(df_out) <- c('grp_id', 'propmz', 'mpc', 'proba')
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235 DBI::dbWriteTable(con, name='probmetab_results', value=df_out, row.names=FALSE)
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236
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237 }
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238
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239
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240 }
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241
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242 add_extra_table_elucidation('metfrag_results', opt$metfrag_result, con, filter_Score=0.6, filter_Rank=NA)
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243 add_extra_table_elucidation('sirius_csifingerid_results', opt$sirius_csifingerid_result, con, filter_Score=NA, filter_Rank=5)
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244 add_probmetab(opt$probmetab_result, con)
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245
1
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246
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247
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248
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249 cmd <- paste('SELECT cpg.grpid, cpg.mz, cpg.mzmin, cpg.mzmax, cpg.rt, cpg.rtmin, cpg.rtmax, c_peaks.cid, ',
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250 'c_peaks.mzmin AS c_peak_mzmin, c_peaks.mzmax AS c_peak_mzmax, ',
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251 'c_peaks.rtmin AS c_peak_rtmin, c_peaks.rtmax AS c_peak_rtmax, s_peak_meta.*, fileinfo.filename, fileinfo.nm_save ',
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252 'FROM c_peak_groups AS cpg ',
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253 'LEFT JOIN c_peak_X_c_peak_group AS cXg ON cXg.grpid=cpg.grpid ',
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254 'LEFT JOIN c_peaks on c_peaks.cid=cXg.cid ',
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255 'LEFT JOIN c_peak_X_s_peak_meta AS cXs ON cXs.cid=c_peaks.cid ',
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256 'LEFT JOIN s_peak_meta ON cXs.pid=s_peak_meta.pid ',
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257 'LEFT JOIN fileinfo ON s_peak_meta.fileid=fileinfo.fileid')
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258
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259 print(cmd)
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260 cpeakgroup_msms <- DBI::dbGetQuery(con, cmd)
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261
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262 write.table(cpeakgroup_msms, file.path(opt$out_dir, 'cpeakgroup_msms.tsv'), row.names=FALSE, sep='\t')