Mercurial > repos > tomnl > assess_purity_msms

annotate create_msp.R @ 13:eea94e398c26 draft

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planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit 97c9122c9af9ddca3a2498185ce8c7919c0df03a
author tomnl
date Tue, 08 May 2018 05:30:13 -0400
parents e5f627fd21e8
children fa5838760aee
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1 suppressWarnings(suppressPackageStartupMessages(require(optparse,quietly = T)))
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2 suppressWarnings(suppressPackageStartupMessages(require(msPurity)))
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3 print(sessionInfo())
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4 # Get the parameter
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5 option_list <- list(
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6 make_option(c("-i","--purity"),type="character"),
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7 make_option(c("-p","--ppm"),type="numeric"),
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8 make_option(c("-m","--mode"),type="character")
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9 )
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10 opt <- parse_args(OptionParser(option_list=option_list))
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12 print(opt)
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14 load(opt$purity)
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16 grped_df <- pa@grped_df
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18 msms <- pa@grped_ms2
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20 puritydf <- pa@puritydf
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26 grped_df$fileid <- sapply(grped_df$filename, function(x) which(basename(pa@fileList)==x))
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28 puritydf$fileid <- sapply(puritydf$filename, function(x) which(basename(pa@fileList)==x))
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30 selfrag <- as.numeric(unique(grped_df$grpid))
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32 of <- file(description = "outfile.msp", open = "w+a")
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34 write.msp <- function(name,precmz,prectype,spectra,ofile){
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36 cat(paste("NAME: ", name, "\r\n", sep = ""), file = ofile)
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38 cat(paste("PRECURSORMZ: ", precmz , "\r\n", sep = ""), file = ofile)
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40 #cat(paste("PRECURSORTYPE: ", prectype, "\r\n", sep = ""), file = ofile) # No adducts? Annotation
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42 cat("Comment:\r\n", file = ofile)
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44 cat(paste("Num Peaks: ", nrow(spectra), "\r\n", sep = ""), file = ofile)
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46 cat(paste(paste(spectra[,1], spectra[,2], sep = "\t"), sep = "\r\n"), sep = "\r\n", file = ofile)
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48 cat("\r\n", file = ofile)
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49 }
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51 for(i in selfrag){
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53 j <- which(grped_df$grpid==i)
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55 spec <- msms[[as.character(i)]]
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57 if (length(j)>1){
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59 grpd <- grped_df[j,]
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61 if (opt$mode=="all"){
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63 for(jj in 1:length(j)){
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65 idj <- paste(i,jj,sep=".")
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67 specj <- spec[[jj]]
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69 grpdj <- grpd[jj,]
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71 name = paste(i, grpdj$sample, grpdj$pid, sep='-')
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73 write.msp(name,grpdj$precurMtchMZ,"",specj,of)
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74 }
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76 }else{
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78 prec_int <- sapply(grpd$precurMtchID, function(x) puritydf[ which(puritydf$seqNum==x & puritydf$fileid==grpd$fileid[1]), "precursorIntensity"] )
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80 if (opt$mode=="max"){
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82 idx <- which(prec_int==max(prec_int))
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84 grpd <- grpd[idx,]
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85 name = paste(i, grpd$sample, grpd$pid, sep='-')
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86 write.msp(name,grpd$precurMtchMZ,"",specj[[idx]], of)
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87 }
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89 if (opt$mode=="average"){
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91 file_weights <- prec_int/prec_int[which(prec_int==min(prec_int))] # spectra of the most intense precursor, largest weight
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93 merged_msms <- do.call("rbind", spec)
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95 colnames(merged_msms) <- c("mz","int")
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96
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97 file_weights <-rep(file_weights,sapply(spec,nrow))
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98
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99 merged_msms <- data.frame(cbind(merged_msms,file_weights))
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100
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101 umzs <- sort(merged_msms$mz,index.return=T)$ix
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102
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103 merged_msms <- merged_msms[umzs,]
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104
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105 umzs <- merged_msms$mz
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106
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107 mz_groups <- list() # mz windows to bind
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108
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109 mz_grouped <- c() # used mzs
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110
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111 ppm <- opt$ppm # ppm level to bind mzs
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112
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113 for(y in 1:length(umzs)){ # spectra averaging
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114
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115 z <- umzs[y]
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116
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117 if(!(z %in% mz_grouped)){
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118
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119 mz_range <- z*(ppm/1e6)
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120
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121 mz_range <- c(z-mz_range,z+mz_range)
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122
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123 mz_group <- which(umzs>mz_range[1] & umzs<mz_range[2])
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124
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125 if(length(mz_group)>1){
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126
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127 zz <- umzs[max(mz_group)]
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128
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129 mz_range <- zz*(ppm/1e6)
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130
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131 mz_range <- c(zz-mz_range,zz+mz_range)
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132
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133 mz_group2 <- which(umzs>mz_range[1] & umzs<mz_range[2])
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134
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135 mz_group <- append(mz_group,mz_group2)
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136 }
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137
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138 mz_group <- unique(mz_group)
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139
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140 mz_grouped <- append(mz_grouped,umzs[mz_group])
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141
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142 mz_group <- list(mz_group)
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143
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144 mz_groups <- append(mz_groups,mz_group)
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145 }
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146 }
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147
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148 averaged_spec <- t(sapply(mz_groups,function(x){
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149
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150 if(length(x)==1){
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151
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152 mz <- merged_msms$mz[x]
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153
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154 nint <- merged_msms[x,]
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155
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156 nint <- nint$int*nint$file_weights
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157
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158 }else{
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159
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160 mz <- mean(merged_msms$mz[x])
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161
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162 nint <- sum(sapply(x,function(y){
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163 nint <- merged_msms[y,]
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164 nint <- nint$int*nint$file_weights
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165 }))
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166 }
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167 return(c(mz,nint))
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168 }))
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169
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170 write.msp(i,mean(grpd$precurMtchMZ),"",averaged_spec,of)
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171
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172 }
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173 }
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174 }else{
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175 spec <- spec[[1]]
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176
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177 grpd <- grped_df[j,]
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178 name = paste(i, grpd$sample, grpd$pid, sep='-')
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179 write.msp(name,grpd$precurMtchMZ,"",spec,of)
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180 }
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181 }
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182
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183