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annotate lib.r @ 0:e13ec2c3fabe draft

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author mmonsoor
date Mon, 04 Jul 2016 04:29:25 -0400
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1 # lib.r ProbMetab version="1.0.0"
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2 # Author: Misharl Monsoor ABIMS TEAM mmonsoor@sb-roscoff.fr
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3 # Contributors: Yann Guitton and Jean-francois Martin
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4
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5
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6 ##Main probmetab function launch by the Galaxy ProbMetab wrapper
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7 probmetab = function(xa, xaP, xaN, variableMetadata, variableMetadataP, variableMetadataN, listArguments){
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8 ##ONE MODE ACQUISITION##
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9 if(listArguments[["mode_acquisition"]]=="one") {
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10 comb=NULL
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11
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12 #Get the polarity from xa object
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13 polarity=xa@polarity
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14 #SNR option
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15 if ("xsetnofill" %in% names(listArguments)) {
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16 load(listArguments[["xsetnofill"]])
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17 xsetnofill=xset
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18 }
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19 else{
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20 xsetnofill=NULL
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21 }
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22 #Exclude samples
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23 if ("toexclude" %in% names(listArguments)) {
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24 toexclude=listArguments[["toexclude"]]
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25 }
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26 else {
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27 toexclude=NULL
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28 }
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29 ionAnnot=get.annot(xa, polarity=polarity, allowMiss=listArguments[["allowMiss"]],xset=xsetnofill,toexclude=toexclude)
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30 comb=NULL
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31 }
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32
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33 ##TWO MODES ACQUISITION##
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34 #Mode annotatediffreport
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35 else if(listArguments[["inputs_mode"]]=="two"){
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36 ##Prepare the objects that will be used for the get.annot function
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37 comb=1
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38
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39
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40 xsetPnofill=NULL
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41 xsetNnofill=NULL
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42 # TODO: a reactiver
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43 #if ("xsetPnofill" %in% names(listArguments)) {
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44 # load(listArguments[["xsetPnofill"]])
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45 # xsetPnofill=xset
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46 #}
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47 #if ("xsetNnofill" %in% names(listArguments)) {
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48 # load(listArguments[["xsetNnofill"]])
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49 # xsetNnofill=xset
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50 #}
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51 # include CAMERA non-annotated compounds, and snr retrieval
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52 # comb 2+ - used on Table 1
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53 ionAnnotP2plus = get.annot(axP, allowMiss=listArguments[["allowMiss"]], xset=xsetPnofill,toexclude=listArguments[["toexclude"]])
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54 ionAnnotN2plus = get.annot(axN, polarity="negative", allowMiss=listArguments[["allowMiss"]], xset=xsetNnofill,toexclude=listArguments[["toexclude"]])
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55 ionAnnot = combineMolIon(ionAnnotP2plus, ionAnnotN2plus)
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56 print(sum(ionAnnot$molIon[,3]==1))
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57 print(sum(ionAnnot$molIon[,3]==0))
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58 write.table(ionAnnot[1], sep="\t", quote=FALSE, row.names=FALSE, file="CombineMolIon.tsv")
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59 #Merge variableMetadata Negative and positive acquisitions mode
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60
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61
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62 #Mode combinexsannos TODO bug avec tableau issus de combinexsannos
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63 #else {
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64 #load(listArguments[["image_combinexsannos"]])
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65 #image_combinexsannos=cAnnot
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66 ##Prepare the objects that will be used for the combineMolIon function
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67 #load(listArguments[["image_pos"]])
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68 #image_pos=xa
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69 #ionAnnot=combineMolIon(peaklist=cAnnot, cameraobj=image_pos, polarity="pos")
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70 #}
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71
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72 }
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73
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74 ##DATABASE MATCHING##
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75 if (listArguments[["kegg_db"]]=="KEGG"){
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76 DB=build.database.kegg(orgID = NULL)
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77 }
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78 else{
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79 table_list <<- NULL
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80 ids=strsplit(listArguments[["kegg_db"]],",")
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81 ids=ids[[1]]
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82 if(length(ids)>1){
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83 for(i in 1:length(ids)){
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84 table_list[[i]] <- build.database.kegg(ids[i])
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85 }
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86 db_table=do.call("rbind",table_list)
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87 DB=unique(db_table)
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88 }
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89 else{
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90 DB=build.database.kegg(listArguments[["kegg_db"]])
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91 }
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92 }
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93 #Matching des mass exactes mesurees avec les masses des compounds KEGG (pas M+H ou M-H)
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94 reactionM = create.reactionM(DB, ionAnnot, ppm.tol=listArguments[["ppm_tol"]])
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95 ##PROBABILITY RANKING##
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96 # number of masses with candidates inside the fixed mass window
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97 # and masses with more than one candidate
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98 length(unique(reactionM[reactionM[,"id"]!="unknown",1]))
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99 sum(table(reactionM[reactionM[,"id"]!="unknown",1])>1)
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100 #if (listArguments[["useIso"]]){
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101 #BUG TODO
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102 # Calculate the ratio between observed and theoretical isotopic patterns.
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103 # If you don't have an assessment of carbon offset to carbon number prediction
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104 # skip this step and use the reactionM as input to weigthM function.
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105 #isoPatt < incorporate.isotopes(comb2plus, reactionM, , samp=12:23, DB=DB)
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106 # calculate the likelihood of each mass to compound assignment using mass accuracy,and isotopic pattern, when present
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107 #wl < weightM(isoPatt,intervals=seq(0,1000,by=500), offset=c(3.115712, 3.434146, 2.350798))
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108
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109 #isoPatt=incorporate.isotopes(ionAnnot, reactionM,comb=comb,var=listArguments[["var"]],DB=DB)
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110
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111 #wl = weightM(reactionM, useIso=true)
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112 #}
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113 #else {
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114 #wl = weightM(reactionM, useIso=FALSE)
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115 #}
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116 wl =weightM(reactionM, useIso=FALSE)
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117 w = design.connection(reactionM)
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118 # Probability calculations
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119 x = 1:ncol(wl$wm)
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120 y = 1:nrow(wl$wm)
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121 conn = gibbs.samp(x, y, 5000, w, wl$wm)
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122 ansConn = export.class.table(conn, reactionM, ionAnnot, DB=DB,html=listArguments[["html"]],filename="AnalysisExample",prob=listArguments[["prob"]])
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123 if(listArguments[["html"]]){
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124 #Zip the EICS plot
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125 system(paste('zip -r "Analysis_Report.zip" "AnalysisExample_fig"'))
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126 }
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127
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128 # calculate the correlations and partial correlations and cross reference then with reactions
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129 mw=which(w==1,arr.ind=TRUE)
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130 #reac2cor function : Use the intensity of putative molecules in repeated samples to calculate correlations and partial
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131 #correlation in a user defined threshold of false discovery rate for significance testing. After the
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132 #correlation test the function also overlay significant correlations with all putative reactions between
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133 #two masses.
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134 #It generates a list of estimated correlations and reactions.
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135 corList=reac2cor(mw,ansConn$classTable,listArguments[["opt"]],listArguments[["corths"]],listArguments[["corprob"]],listArguments[["pcorprob"]])
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136 ans=list("ansConn"=ansConn,"corList"=corList)
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137 #Generate the siff table for CytoScape
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138 cytoscape_output(corList,ansConn)
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139
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140
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141 #Execute the merge_probmetab function to merge the variableMetadata table and annotations from ProbMetab results
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142
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143 if(listArguments[["mode_acquisition"]]=="one") {
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144 #Retrocompatibility with previous annotateDiffreport variableMetadata dataframe (must replace mzmed column by mz, and rtmed by rt)
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145 names(variableMetadata)[names(variableMetadata)=="mzmed"] <- "mz"
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146 names(variableMetadata)[names(variableMetadata)=="rtmed"] <- "rt"
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147 variableM=merge_probmetab(variableMetadata, ansConn)
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148 write.table(variableM, sep="\t", quote=FALSE, row.names=FALSE, file="variableMetadata.tsv")
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149 } else if (listArguments[["mode_acquisition"]]=="two") {
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150 #Retrocompatibility with previous annotateDiffreport variableMetadata dataframe (must replace mzmed column by mz, and rtmed by rt)
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151 names(variableMetadataP)[names(variableMetadata)=="mzmed"] <- "mz"
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152 names(variableMetadataP)[names(variableMetadata)=="rtmed"] <- "rt"
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153 names(variableMetadataN)[names(variableMetadata)=="mzmed"] <- "mz"
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154 names(variableMetadataN)[names(variableMetadata)=="rtmed"] <- "rt"
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155 variableMP=merge_probmetab(variableMetadataP, ansConn)
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156 write.table(variableMP, sep="\t", quote=FALSE, row.names=FALSE, file="variableMetadata_Positive.tsv")
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157 variableMN=merge_probmetab(variableMetadataN, ansConn)
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158 write.table(variableMN, sep="\t", quote=FALSE, row.names=FALSE, file="variableMetadata_Negative.tsv")
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159 }
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160
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161 return(ans)
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162
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163 }
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164
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165 ##Function that generates a siff table for CytoScape
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166 cytoscape_output=function(corList,ansConn){
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167 signif_cor=as.data.frame(corList$signif.cor)
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168 classTable=as.data.frame(ansConn$classTable)
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169 #Siff table
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170 siff_table=cbind(signif_cor["node1"],signif_cor["cor"],signif_cor["node2"])
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171 #attribute table output for Cytoscape
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172
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173 ## START Code part from the export2cytoscape function of ProbMetab written by Ricardo R. Silva
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174 for (i in 1:nrow(classTable)) if (classTable[i, 1] == ""){
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175 classTable[i, c(1, 4, 6, 7)] <- classTable[i - 1, c(1, 4, 6, 7)]
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176 }
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177 msel <- as.matrix(classTable[, 1:7])
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178 msel <- cbind(msel[, 6], msel[,-6])
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179 colnames(msel)[1] <- "Id"
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180 msel[, 1] <- sub("^\\s+", "", msel[, 1])
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181 colnames(msel)[1] <- "Id"
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182 ids <- unique(msel[, 1])
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183 attrMatrix <- matrix("", nrow = length(ids), ncol = ncol(msel)-1)
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184 for (i in 1:length(ids)) {
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185 attrMatrix[i, 1] <- unique(msel[msel[, 1] == ids[i],
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186 2])
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187 attrMatrix[i, 2] <- paste("[", paste(msel[msel[,
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188 1] == ids[i], 3], collapse = ", "), "]", sep = "")
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189 attrMatrix[i, 3] <- paste("[", paste(msel[msel[,
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190 1] == ids[i], 4], collapse = ", "), "]", sep = "")
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191 attrMatrix[i, 4] <- unique(msel[msel[, 1] == ids[i],
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192 5])
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193 attrMatrix[i, 5] <- paste("[", paste(msel[msel[,
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194 1] == ids[i], 6], collapse = ", "), "]", sep = "")
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195 attrMatrix[i, 6] <- unique(msel[msel[, 1] == ids[i],
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196 7])
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197 }
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198 ids <- as.numeric(unique(msel[, 1]))
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199 attrMatrix <- cbind(ids, attrMatrix)
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200 colnames(attrMatrix) <- colnames(msel)
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201 ## END Code part from the export2cytoscape function of ProbMetab writieen by Ricardo R. Silva
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202 write.table(attrMatrix, sep="\t", quote=FALSE, row.names=FALSE, file="Analysis_Report.tsv")
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203 write.table(siff_table, sep="\t", quote=FALSE, row.names=FALSE, file="sif.tsv")
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204
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205 return(attrMatrix)
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206 }
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207
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208 ##Functions written by Jean-Francois Martin
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209
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210 deter_ioni <- function (aninfo, pm)
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211 {
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212 # determine ionisation in ProbMetab result file, used in function merge_probmetab
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213 # input : for 1 ion, aninfo = string with m/z rt and CAMERA annotation from ProbMetab result file
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214 # if the difference between m/z and the probmetab proposed mass is ~1 we use the sign (positive or negative) of this diference
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215 # to define the type of ionisation
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216 # If adduct or fragment was detected, therefore diff >>1 and so, we search for substring "+" ou "2+" ou "3+" ou "-"...
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217 # to define the type of ionisation
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218 # aninfo : vecteur of character resulting of the parsing(sep="#") of the probmetab annotation
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219 if (round(abs(as.numeric(aninfo[1]) - pm),0) ==1) {
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220 if (as.numeric(aninfo[1]) - pm <0) {esi <- "n"} else {esi <- "p"}
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221 } else
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222 if (!is.na(aninfo[4])) {
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223 anstr <- aninfo[4]
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224 # cat(anstr)
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225 if ((grepl("]+",anstr,fixed=T)==T) || (grepl("]2+",anstr,fixed=T)==T) || (grepl("]3+",anstr,fixed=T)==T)) { esi <- "p"}
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226 else
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227 if ((grepl("]-",anstr,fixed=T)==T) || (grepl("]2-",anstr,fixed=T)==T) || (grepl("]3-",anstr,fixed=T)==T)) { esi <- "n"}
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228 # cat(" ioni ",esi,"\n")
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229 } else
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230 { esi <- "u"}
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231
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232 return(esi)
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233 }
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234
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235
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236 merge_probmetab <- function(metaVar,ansConn) {
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237 ## Parse ProbMetab information result file and merge in variable_metaData initial file
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238 ## inputs :
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239 ## metaVar : data.frame of metadataVariable input of probmetab function
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240 ## ansConn : data.frame of ProbMetab result
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241 ## output : dataframe with Probmetab results merge with variableMetadata
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242 ## Constante
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243 ## iannot : indice de la colonne annotation dans le resultat de probMetab
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244 iannot <- 4
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245
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246 ## definition of an unique identification of ions mz with 3 decimals and rt(sec) with 1 decimal to avoid
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247 ## duplicate ions name in the diffreport result file
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248 ions <- paste ("M",round(metaVar$mz,3),"T",round(metaVar$rt,1),sep="")
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249 metaVar <- data.frame(ions,metaVar)
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250
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251 ###### Result data.frame from ProbMetab result list
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252 an_ini <- ansConn$classTable
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253
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254 ## Suppression of rows without mz and rt or unknown and columns of intensities
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255 ## COLUMNS SUBSCRIPTS HAVE TO BE CHECKED WITh DIFFERENT RESULTS FILES
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256 an <- an_ini[(an_ini[,2]!="unknown"),c(1,2,3,7)]
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257 ## initialisation of vectors receiving the result of the parse of the column annotation (subscrip iannot)
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258 mz <- rep(0,dim(an)[1])
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259 rt <- rep(0,dim(an)[1])
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260 propmz <- rep(0,dim(an)[1])
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261 ioni <- rep("u",dim(an)[1])
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262
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263 ## parse the column annotation and define ionisation mode
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264 for (i in 1:dim(an)[1]) {
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265 if (an[i,1] != "") {
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266 info_mzrt <- unlist(strsplit(an[i,iannot],"#"))
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267 propmz[i] <- as.numeric(an[i,1])
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268 mz[i] <- as.numeric(info_mzrt[1])
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269 rt[i] <- as.numeric(info_mzrt[2])
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270 ioni[i] <- deter_ioni(info_mzrt,as.numeric(an[i,1]))
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271 }
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272 else {
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273 propmz[i] <- as.numeric(propmz[i-1])
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274 mz[i] <- as.numeric(mz[i-1])
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275 rt[i] <- as.numeric(rt[i-1])
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276 ioni[i] <- ioni[i-1]
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277 }
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278 }
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279
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280 ## definition of an unique identification of ions : mz with 3 decimals and rt(sec) with 1 decimal
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281 ## The same as for the metadataVariable data.frame to match with.
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282 ions <- paste ("M",round(mz,3),"T",round(rt,1),sep="")
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283 an <- data.frame(ions,ioni,propmz,mz,rt,an)
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284
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285 ## transposition of the different probmetab annotations which are in different rows in the initial result data.frame
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286 ## on only 1 row separated with a ";"
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287 li <- as.matrix(table(an$propmz))
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288 li <- data.frame(dimnames(li)[1],li)
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289 dimnames(li)[[2]][1] <- "propmz"
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290 ions <- rep("u",dim(li)[1])
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291 propmz <- rep(0,dim(li)[1])
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292 mpc <- rep("c",dim(li)[1])
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293 proba <- rep("p",dim(li)[1])
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294 c <- 0
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295 while (c < dim(li)[1]) {
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296 c <- c + 1
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297 suban <- an[an$propmz==li[c,1],]
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298 ions[c] <- as.character(suban[1,1])
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299 propmz[c] <- as.numeric(suban[1,3])
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300 mpc[c] <- paste(suban[,7],collapse=";")
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301 proba[c] <- paste(as.character(suban[,8]),collapse=";")
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302 }
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303
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304 ## Creation of the data.frame with 1 row per ions
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305 anc <- data.frame(ions,propmz,mpc,proba)
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306 anc <- anc[order(anc[,1]),]
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307
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308 metaVarFinal <- merge(metaVar, anc, by.x=1, by.y=1, all.x=T, all.y=T)
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309 metaVarFinal <- metaVarFinal[,-1]
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310 #write.table(metaVarFinal,file="res.txt", sep="\t", row.names=F, quote=F)
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311
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312 return (metaVarFinal)
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313 }
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314
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315 # RETROCOMPATIBILITE avec ancienne version de annotate
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316 getVariableMetadata = function(xa) {
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317 # --- variableMetadata ---
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318 peakList=getPeaklist(xa)
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319 peakList=cbind(groupnames(xa@xcmsSet),peakList); colnames(peakList)[1] = c("name");
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320 variableMetadata=peakList[,!(colnames(peakList) %in% c(sampnames(xa@xcmsSet)))]
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321 variableMetadata$name= paste("M",round(variableMetadata$mz),"T",round(variableMetadata$rt),sep="")
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322 return (variableMetadata)
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323 }