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changeset 5:b8d4129dd2a6 draft

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planemo upload for repository https://github.com/workflow4metabolomics/metaMS commit c7a518686137f6d62b7415715152e8d5a9953ed7
author yguitton
date Fri, 06 Sep 2019 06:09:10 -0400
parents c10824185547
children 286ebb9f6e84
files lib_metams.r metaMS_runGC.r test-data/W4M0004_database_small.msp test-data/dataMatrix.tsv test-data/peakspectra.msp test-data/peaktable.tsv test-data/runGC.RData test-data/variableMetadata.tsv
diffstat 8 files changed, 111 insertions(+), 83 deletions(-) [+]
line wrap: on
line diff
--- a/lib_metams.r	Wed Jul 03 05:14:32 2019 -0400
+++ b/lib_metams.r	Fri Sep 06 06:09:10 2019 -0400
@@ -162,13 +162,13 @@
 ##ADDITIONS FROM Y. Guitton
 getBPC <- function(file,rtcor=NULL, ...) {
     object <- xcmsRaw(file)
-	sel <- profRange(object, ...)
-	cbind(if (is.null(rtcor)) object@scantime[sel$scanidx] else rtcor ,xcms:::colMax(object@env$profile[sel$massidx,sel$scanidx,drop=FALSE]))
+    sel <- profRange(object, ...)
+    cbind(if (is.null(rtcor)) object@scantime[sel$scanidx] else rtcor ,xcms:::colMax(object@env$profile[sel$massidx,sel$scanidx,drop=FALSE]))
 }
 
 getBPC2s <- function (files, xset = NULL, pdfname="BPCs.pdf", rt = c("raw","corrected"), scanrange=NULL) {
     require(xcms)
-                   
+
     #create sampleMetadata, get sampleMetadata and class
     if(!is.null(xset)) {
     	#When files come from XCMS3 directly before metaMS
@@ -184,10 +184,10 @@
     }
 
     N <- dim(sampleMetadata)[1]
-    TIC <- vector("list",N)
+    BPC <- vector("list",N)
 
     for (j in 1:N) {
-        TIC[[j]] <- getBPC(files[j])
+        BPC[[j]] <- getBPC(files[j])
         #good for raw 
         # seems strange for corrected
         #errors if scanrange used in xcmsSetgeneration
@@ -196,7 +196,7 @@
         }else{
             rtcor <- NULL
         }
-        TIC[[j]] <- getBPC(files[j],rtcor=rtcor)
+        BPC[[j]] <- getBPC(files[j],rtcor=rtcor)
     }
 
     pdf(pdfname,w=16,h=10)
@@ -204,8 +204,10 @@
     lty = 1:N
     pch = 1:N
     #search for max x and max y in BPCs
-    xlim = range(sapply(TIC, function(x) range(x[,1])))
-    ylim = range(sapply(TIC, function(x) range(x[,2])))
+
+    xlim = range(sapply(BPC, function(x) range(x[,1])))
+    ylim = range(sapply(BPC, function(x) range(x[,2])))
+
     ylim = c(-ylim[2], ylim[2])
 
     ##plot start
@@ -216,15 +218,15 @@
                 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",class[k]," vs ",class[l], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
                 colvect<-NULL
                 for (j in 1:length(classnames[[k]])) {
-                    tic <- TIC[[classnames[[k]][j]]]
-                    # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
-                    points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
+                    bpc <- BPC[[classnames[[k]][j]]]
+                    # points(bpc[,1]/60, bpc[,2], col = cols[i], pch = pch[i], type="l")
+                    points(bpc[,1]/60, bpc[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
                     colvect<-append(colvect,cols[classnames[[k]][j]])
                 }
                 for (j in 1:length(classnames[[l]])) {
                     # i=class2names[j]
-                    tic <- TIC[[classnames[[l]][j]]]
-                    points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
+                    bpc <- BPC[[classnames[[l]][j]]]
+                    points(bpc[,1]/60, -bpc[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
                     colvect<-append(colvect,cols[classnames[[l]][j]])
                 }
                 legend("topright",paste(gsub("(^.+)\\..*$","\\1",basename(files[c(classnames[[k]],classnames[[l]])]))), col = colvect, lty = lty, pch = pch)
@@ -239,15 +241,15 @@
         plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",class[k],"vs",class[l], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
 
         for (j in 1:length(classnames[[k]])) {
-            tic <- TIC[[classnames[[k]][j]]]
-            # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
-            points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
+            bpc <- BPC[[classnames[[k]][j]]]
+            # points(bpc[,1]/60, bpc[,2], col = cols[i], pch = pch[i], type="l")
+            points(bpc[,1]/60, bpc[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
             colvect<-append(colvect,cols[classnames[[k]][j]])
         }
         for (j in 1:length(classnames[[l]])) {
             # i=class2names[j]
-            tic <- TIC[[classnames[[l]][j]]]
-            points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
+            bpc <- BPC[[classnames[[l]][j]]]
+            points(bpc[,1]/60, -bpc[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
             colvect<-append(colvect,cols[classnames[[l]][j]])
         }
         legend("topright",paste(gsub("(^.+)\\..*$","\\1",basename(files[c(classnames[[k]],classnames[[l]])]))), col = colvect, lty = lty, pch = pch)
@@ -255,14 +257,16 @@
     
     if (length(class)==1){
         k=1
-		ylim = range(sapply(TIC, function(x) range(x[,2])))
+
+		ylim = range(sapply(BPC, function(x) range(x[,2])))
+
         colvect<-NULL
         plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",class[k], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
 
         for (j in 1:length(classnames[[k]])) {
-            tic <- TIC[[classnames[[k]][j]]]
-            # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
-            points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
+            bpc <- BPC[[classnames[[k]][j]]]
+            # points(bpc[,1]/60, bpc[,2], col = cols[i], pch = pch[i], type="l")
+            points(bpc[,1]/60, bpc[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
             colvect<-append(colvect,cols[classnames[[k]][j]])
         }
         legend("topright",paste(gsub("(^.+)\\..*$","\\1",basename(files[c(classnames[[k]])]))), col = colvect, lty = lty, pch = pch)
@@ -297,7 +301,6 @@
     TIC <- vector("list",N)
 
     for (i in 1:N) {
-        cat(files[i],"\n")
         if (!is.null(xcmsSet) && rt == "corrected")
             rtcor <- xcmsSet@rt$corrected[[i]]
         else
@@ -318,7 +321,7 @@
     if (length(class)>2){
         for (k in 1:(length(class)-1)){
             for (l in (k+1):length(class)){
-                print(paste(class[k],"vs",class[l],sep=" ")) 
+                cat(paste(class[k],"vs",class[l],"\n",sep=" ")) 
                 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",class[k]," vs ",class[l], sep=""), xlab = "Retention Time (min)", ylab = "TIC")
                 colvect<-NULL
                 for (j in 1:length(classnames[[k]])) {
@@ -500,4 +503,4 @@
 		}
 		graphics.off()
 	}#end  for unkn[l]
-}#end function
\ No newline at end of file
+}#end function
--- a/metaMS_runGC.r	Wed Jul 03 05:14:32 2019 -0400
+++ b/metaMS_runGC.r	Fri Sep 06 06:09:10 2019 -0400
@@ -194,7 +194,7 @@
 #runGC accept either a list of files a zip folder or an xset object from xcms.xcmsSet tool
 #From xset is an .RData file necessary to use the xcmsSet object generated by xcms.xcmsSet given by previous tools
 if (!is.null(args$singlefile_galaxyPath)){
-    cat("Loading datas from XCMS file(s)...\n")
+    cat("Loading datas from XCMS files...\n")
     load(args$singlefile_galaxyPath)
     
     #Transform XCMS object if needed
@@ -207,6 +207,12 @@
             stop(error_message)
         }
     }
+    #Verify that there are more than 1 file (can't run metaMS on only 1 file)
+    if(length(rownames(xdata@phenoData)) < 2){
+        error_message="You need more than 1 file to be able to run metaMS"
+        print(error_message)
+        stop(error_message)
+    }
 
     #xset from xcms.xcmsSet is not well formatted for metaMS this function do the formatting
     if (class(xset)=="xcmsSet"){
@@ -253,7 +259,7 @@
         
         #default settings for GC from Wehrens et al
         cat("Process runGC with metaMS package...\n\n")
-        print(str(TSQXLS.GC))  
+        print(str(TSQXLS.GC))
         resGC<-runGC(xset=xsetCAM,settings=TSQXLS.GC, rtrange=rtrange, DB= DBgc, removeArtefacts = TRUE, 
                     findUnknowns = TRUE, returnXset = TRUE, RIstandards = RIarg, nSlaves = nSlaves)
     } else {
@@ -328,4 +334,12 @@
 objects2save <- c("resGC", "xset", "singlefile", "zipfile", "DBgc")
 save(list = objects2save[objects2save %in% ls()], file = "runGC.RData")
 
-cat("\nEnd of '", modNamC, "' Galaxy module call: ", as.character(Sys.time()), "\n", sep = "")
\ No newline at end of file
+cat("\nEnd of '", modNamC, "' Galaxy module call: ", as.character(Sys.time()), "\n", sep = "")
+
+#WARNING if user has CDF files (not yet good for plotting)
+files <- paste("./",names(singlefile),sep="")
+if(MSnbase:::isCdfFile(files)){
+    warning_message <- "You have CDF files, for the moment you can't obtain plot after runGC! A new update will follow with the good correction"
+    warning(warning_message)
+    cat(paste("\n","/!\\Warning/!\\",warning_message,sep="\n"))
+}
\ No newline at end of file
--- a/test-data/W4M0004_database_small.msp	Wed Jul 03 05:14:32 2019 -0400
+++ b/test-data/W4M0004_database_small.msp	Fri Sep 06 06:09:10 2019 -0400
@@ -1,8 +1,11 @@
 Name: Citric acid, 4TMS
-DB.idx: 2
+DB.idx: 1
+RI: 1803.92
+Formula: C18H40O7Si4
+monoMW: 480.848
 rt: 26.388
+std.rt: 0.0033
 Class: Standard
-std.rt: 0.0033
 Num Peaks: 306
  51  182440;  53  944503;  54  369474;  55  3340984;  56  631621; 
  57  1917866;  58  4022998;  59  7124250;  60  1136187;  61  3360226; 
@@ -68,10 +71,13 @@
  449  29707; 
 
 Name: D-Mannitol, 6TMS
-DB.idx: 3
+DB.idx: 2
+RI: 1916
+Formula: C24H62O6Si6
+monoMW: 620
 rt: 28.581
+std.rt: 0.003
 Class: Standard
-std.rt: 0.003
 Num Peaks: 262
  53  489021;  54  603836;  55  1296110;  56  240694;  57  468516; 
  58  1361419;  59  5385271;  60  600415;  61  685447;  62  50899; 
@@ -128,10 +134,13 @@
  435  116595;  437  17236; 
 
 Name: Ribitol, 5TMS
-DB.idx: 4
+DB.idx: 3
+RI: 1712.74
+Formula: C20H52O5Si5
+monoMW: 512.052
 rt: 24.487
+std.rt: 0.0029
 Class: Standard
-std.rt: 0.0029
 Num Peaks: 236
  53  484493;  54  695945;  55  1354523;  56  372585;  57  610381; 
  58  1975838;  59  7252890;  60  668667;  61  963183;  62  72158; 
@@ -183,8 +192,9 @@
  427  4882;
 
 Name: Glycine, 3TMS
-DB.idx: 5
+DB.idx: 4
 RI: 1302.682
+Formula: C11H29NO2Si3
 monoMW: 291.610
 rt: 13.965
 std.rt: 0.0033
@@ -208,10 +218,10 @@
  278  137402;  279  34431;  367  3442; 
 
 Name: Pyroglutamic acid, 2TMS
-DB.idx: 6
+DB.idx: 5
 RI: 1650.417
 Formula: C11H23NO3Si2
-MW: 273.477
+monoMW: 273.477
 rt: 19.513
 std.rt: 0.0035
 Class: Standard
@@ -250,10 +260,10 @@
  346  77810;  348  24720;  420  13841; 
 
 Name: Alanine, 3TMS
-DB.idx: 7
+DB.idx: 6
 RI: 1360.504
 Formula: C12H31NO2Si3
-MW: 305.637
+monoMW: 305.637
 rt: 15.323
 std.rt: 0.0026
 Num Peaks: 124
@@ -284,10 +294,10 @@
  292  225705;  293  58740;  305  25278;  306  8768; 
 
 Name: Aspartic acid, 2TMS
-DB.idx: 8
+DB.idx: 7
 RI: 1422.39
 Formula: C10H23NO4Si2
-MW: 277.465
+monoMW: 277.465
 rt: 17.071
 std.rt: 0.0042
 Num Peaks: 116
@@ -317,10 +327,10 @@
  442  2912; 
 
 Name: Tryptamine, 2TMS
-DB.idx: 9
+DB.idx: 8
 RI: 2224.531
 Formula: C16H28N2Si2
-MW: 304.578
+monoMW: 304.578
 rt: 19.044
 std.rt: 0.0032
 Num Peaks: 125
--- a/test-data/dataMatrix.tsv	Wed Jul 03 05:14:32 2019 -0400
+++ b/test-data/dataMatrix.tsv	Fri Sep 06 06:09:10 2019 -0400
@@ -1,10 +1,10 @@
 Name	alg3	alg8	alg7	alg9	alg11	alg2
 Glycine, 3TMS	8986693	18739515	23638072	64542302	73997431	3271105
-Pyroglutamic acid, 2TMS	52421941	117387451	201537792	172306144	173875991	18034050
+Pyroglutamic acid, 2TMS	52421941	117387451	201537792	172306142	173875991	17771445
 Alanine, 3TMS	16302374	40418507	56198912	47836465	75099028	5873408
 Aspartic acid, 2TMS	5491883	30361752	53297090	31703522	43848521	0
 Tryptamine, 2TMS	24418912	21999992	12482634	19565268	29742266	12344352
-Unknown 1	2608558	7958675	10512589	0	0	716439
+Unknown 1	2608558	7958675	10512729	0	0	716439
 Unknown 2	992454	1414530	0	0	0	350707
 Unknown 3	0	47472144	65646101	48115807	0	0
 Unknown 4	0	17508248	9099661	16725736	22787828	0
--- a/test-data/peakspectra.msp	Wed Jul 03 05:14:32 2019 -0400
+++ b/test-data/peakspectra.msp	Fri Sep 06 06:09:10 2019 -0400
@@ -1,10 +1,11 @@
 Name: Glycine, 3TMS
-DB.idx: 5
+DB.idx: 4
 RI: 1302.682
+Formula: C11H29NO2Si3
 monoMW: 291.61
 std.rt: 13.965
 Class: Standard
-DB.idx: 5
+DB.idx: 4
 Num Peaks: 78
  57  316293;  58  608407;  59  2360607;  60  298845;  61  196310; 
  70  169295;  71  161384;  72  648791;  73  11721138;  74  1113027; 
@@ -24,13 +25,13 @@
  278  137402;  279  34431;  367  3442; 
 
 Name: Pyroglutamic acid, 2TMS
-DB.idx: 6
+DB.idx: 5
 RI: 1650.417
 Formula: C11H23NO3Si2
-MW: 273.477
+monoMW: 273.477
 std.rt: 19.513
 Class: Standard
-DB.idx: 6
+DB.idx: 5
 Num Peaks: 158
  51  338626;  52  575985;  53  464956;  54  649153;  55  3336412; 
  56  1197195;  57  2169449;  58  6685191;  59  9081136;  60  1387309; 
@@ -66,13 +67,13 @@
  346  77810;  348  24720;  420  13841; 
 
 Name: Alanine, 3TMS
-DB.idx: 7
+DB.idx: 6
 RI: 1360.504
 Formula: C12H31NO2Si3
-MW: 305.637
+monoMW: 305.637
 std.rt: 15.323
 Class: Manual
-DB.idx: 7
+DB.idx: 6
 Num Peaks: 124
  54  89758;  55  274561;  56  190979;  57  472743;  58  1227701; 
  59  8857202;  60  769050;  61  572383;  62  41693;  66  257757; 
@@ -101,13 +102,13 @@
  292  225705;  293  58740;  305  25278;  306  8768; 
 
 Name: Aspartic acid, 2TMS
-DB.idx: 8
+DB.idx: 7
 RI: 1422.39
 Formula: C10H23NO4Si2
-MW: 277.465
+monoMW: 277.465
 std.rt: 17.071
 Class: Manual
-DB.idx: 8
+DB.idx: 7
 Num Peaks: 116
  53  110556;  54  70748;  55  491989;  56  176719;  57  429061; 
  58  867565;  59  1844082;  60  680229;  61  1783651;  62  153287; 
@@ -135,13 +136,13 @@
  442  2912; 
 
 Name: Tryptamine, 2TMS
-DB.idx: 9
+DB.idx: 8
 RI: 2224.531
 Formula: C16H28N2Si2
-MW: 304.578
+monoMW: 304.578
 std.rt: 19.044
 Class: Manual
-DB.idx: 9
+DB.idx: 8
 Num Peaks: 125
  53  103908;  54  92348;  55  359811;  56  220319;  57  234375; 
  58  577937;  59  3625396;  60  353747;  61  203780;  65  56054; 
--- a/test-data/peaktable.tsv	Wed Jul 03 05:14:32 2019 -0400
+++ b/test-data/peaktable.tsv	Fri Sep 06 06:09:10 2019 -0400
@@ -1,12 +1,12 @@
-"Name"	"DB.idx"	"RI"	"monoMW"	"Class"	"Formula"	"MW"	"std.rt"	"rt.sd"	"rt"	"alg3"	"alg8"	"alg7"	"alg9"	"alg11"	"alg2"
-"Glycine, 3TMS"	5	1302.682	291.61	"Standard"	NA	NA	13.965	0.0267	13.973	8986693	18739515	23638072	64542302	73997431	3271105
-"Pyroglutamic acid, 2TMS"	6	1650.417	NA	"Standard"	"C11H23NO3Si2"	273.477	19.513	0.0247	19.512	52421941	117387451	201537792	172306144	173875991	18034050
-"Alanine, 3TMS"	7	1360.504	NA	"Manual"	"C12H31NO2Si3"	305.637	15.323	0.028	15.332	16302374	40418507	56198912	47836465	75099028	5873408
-"Aspartic acid, 2TMS"	8	1422.39	NA	"Manual"	"C10H23NO4Si2"	277.465	17.071	0.0359	17.09	5491883	30361752	53297090	31703522	43848521	0
-"Tryptamine, 2TMS"	9	2224.531	NA	"Manual"	"C16H28N2Si2"	304.578	19.044	0.036	19.068	24418912	21999992	12482634	19565268	29742266	12344352
-"Unknown 1"	NA	NA	NA	"Unknown"	NA	NA	NA	0.0049	10.488	2608558	7958675	10512589	0	0	716439
-"Unknown 2"	NA	NA	NA	"Unknown"	NA	NA	NA	0.005	11.428	992454	1414530	0	0	0	350707
-"Unknown 3"	NA	NA	NA	"Unknown"	NA	NA	NA	0.0037	13.262	0	47472144	65646101	48115807	0	0
-"Unknown 4"	NA	NA	NA	"Unknown"	NA	NA	NA	0.0032	17.879	0	17508248	9099661	16725736	22787828	0
-"Unknown 5"	NA	NA	NA	"Unknown"	NA	NA	NA	0.0046	17.181	0	15283058	7754880	13107264	19795467	0
-"Unknown 6"	NA	NA	NA	"Unknown"	NA	NA	NA	0.004	13.327	0	5270387	6059689	6659142	0	0
+"Name"	"DB.idx"	"RI"	"Formula"	"monoMW"	"Class"	"std.rt"	"rt.sd"	"rt"	"alg3"	"alg8"	"alg7"	"alg9"	"alg11"	"alg2"
+"Glycine, 3TMS"	4	1302.682	"C11H29NO2Si3"	291.61	"Standard"	13.965	0.0267	13.973	8986693	18739515	23638072	64542302	73997431	3271105
+"Pyroglutamic acid, 2TMS"	5	1650.417	"C11H23NO3Si2"	273.477	"Standard"	19.513	0.0247	19.512	52421941	117387451	201537792	172306142	173875991	17771445
+"Alanine, 3TMS"	6	1360.504	"C12H31NO2Si3"	305.637	"Manual"	15.323	0.028	15.332	16302374	40418507	56198912	47836465	75099028	5873408
+"Aspartic acid, 2TMS"	7	1422.39	"C10H23NO4Si2"	277.465	"Manual"	17.071	0.0359	17.09	5491883	30361752	53297090	31703522	43848521	0
+"Tryptamine, 2TMS"	8	2224.531	"C16H28N2Si2"	304.578	"Manual"	19.044	0.036	19.068	24418912	21999992	12482634	19565268	29742266	12344352
+"Unknown 1"	NA	NA	NA	NA	"Unknown"	NA	0.0049	10.488	2608558	7958675	10512729	0	0	716439
+"Unknown 2"	NA	NA	NA	NA	"Unknown"	NA	0.005	11.428	992454	1414530	0	0	0	350707
+"Unknown 3"	NA	NA	NA	NA	"Unknown"	NA	0.0037	13.262	0	47472144	65646101	48115807	0	0
+"Unknown 4"	NA	NA	NA	NA	"Unknown"	NA	0.0032	17.879	0	17508248	9099661	16725736	22787828	0
+"Unknown 5"	NA	NA	NA	NA	"Unknown"	NA	0.0046	17.181	0	15283058	7754880	13107264	19795467	0
+"Unknown 6"	NA	NA	NA	NA	"Unknown"	NA	0.004	13.327	0	5270387	6059689	6659142	0	0
Binary file test-data/runGC.RData has changed
--- a/test-data/variableMetadata.tsv	Wed Jul 03 05:14:32 2019 -0400
+++ b/test-data/variableMetadata.tsv	Fri Sep 06 06:09:10 2019 -0400
@@ -1,12 +1,12 @@
-Name	DB.idx	RI	monoMW	Class	Formula	MW	std.rt	rt.sd	rt
-Glycine, 3TMS	5	1302.682	291.61	Standard	NA	NA	13.965	0.0267	13.973
-Pyroglutamic acid, 2TMS	6	1650.417	NA	Standard	C11H23NO3Si2	273.477	19.513	0.0247	19.512
-Alanine, 3TMS	7	1360.504	NA	Manual	C12H31NO2Si3	305.637	15.323	0.028	15.332
-Aspartic acid, 2TMS	8	1422.39	NA	Manual	C10H23NO4Si2	277.465	17.071	0.0359	17.09
-Tryptamine, 2TMS	9	2224.531	NA	Manual	C16H28N2Si2	304.578	19.044	0.036	19.068
-Unknown 1	NA	NA	NA	Unknown	NA	NA	NA	0.0049	10.488
-Unknown 2	NA	NA	NA	Unknown	NA	NA	NA	0.005	11.428
-Unknown 3	NA	NA	NA	Unknown	NA	NA	NA	0.0037	13.262
-Unknown 4	NA	NA	NA	Unknown	NA	NA	NA	0.0032	17.879
-Unknown 5	NA	NA	NA	Unknown	NA	NA	NA	0.0046	17.181
-Unknown 6	NA	NA	NA	Unknown	NA	NA	NA	0.004	13.327
+Name	DB.idx	RI	Formula	monoMW	Class	std.rt	rt.sd	rt
+Glycine, 3TMS	4	1302.682	C11H29NO2Si3	291.61	Standard	13.965	0.0267	13.973
+Pyroglutamic acid, 2TMS	5	1650.417	C11H23NO3Si2	273.477	Standard	19.513	0.0247	19.512
+Alanine, 3TMS	6	1360.504	C12H31NO2Si3	305.637	Manual	15.323	0.028	15.332
+Aspartic acid, 2TMS	7	1422.39	C10H23NO4Si2	277.465	Manual	17.071	0.0359	17.09
+Tryptamine, 2TMS	8	2224.531	C16H28N2Si2	304.578	Manual	19.044	0.036	19.068
+Unknown 1	NA	NA	NA	NA	Unknown	NA	0.0049	10.488
+Unknown 2	NA	NA	NA	NA	Unknown	NA	0.005	11.428
+Unknown 3	NA	NA	NA	NA	Unknown	NA	0.0037	13.262
+Unknown 4	NA	NA	NA	NA	Unknown	NA	0.0032	17.879
+Unknown 5	NA	NA	NA	NA	Unknown	NA	0.0046	17.181
+Unknown 6	NA	NA	NA	NA	Unknown	NA	0.004	13.327