Mercurial > repos > tomnl > anticipated_purity_lcms

annotate frag4feature.R @ 0:dc00b7222a3c draft

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planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit f9591483bef88aef71a9f0cc0ffc75cf6eab480c
author tomnl
date Mon, 05 Mar 2018 10:01:25 -0500
parents
children c64891642e41
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0
dc00b7222a3c planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit f9591483bef88aef71a9f0cc0ffc75cf6eab480c
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1 library(msPurity)
dc00b7222a3c planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit f9591483bef88aef71a9f0cc0ffc75cf6eab480c
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2 library(optparse)
dc00b7222a3c planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit f9591483bef88aef71a9f0cc0ffc75cf6eab480c
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3
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4 option_list <- list(
dc00b7222a3c planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit f9591483bef88aef71a9f0cc0ffc75cf6eab480c
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5 make_option(c("-o", "--out_dir"), type="character"),
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6 make_option("--pa", type="character"),
dc00b7222a3c planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit f9591483bef88aef71a9f0cc0ffc75cf6eab480c
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7 make_option("--xset", type="character"),
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8 make_option("--ppm", default=10),
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9 make_option("--plim", default=0.0),
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10 make_option("--convert2RawRT", action="store_true"),
dc00b7222a3c planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit f9591483bef88aef71a9f0cc0ffc75cf6eab480c
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11 make_option("--mostIntense", action="store_true"),
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12 make_option("--cores", default=4),
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13 make_option("--mzML_files", type="character"),
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14 make_option("--galaxy_names", type="character"),
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15 make_option("--grp_peaklist", type="character")
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16 )
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18 # store options
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19 opt<- parse_args(OptionParser(option_list=option_list))
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21 loadRData <- function(rdata_path, name){
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22 #loads an RData file, and returns the named xset object if it is there
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23 load(rdata_path)
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24 return(get(ls()[ls() == name]))
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25 }
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27 # Requires
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28 pa <- loadRData(opt$pa, 'pa')
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29 xset <- loadRData(opt$xset, 'xset')
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31 pa@cores <- opt$cores
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32
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33 if(is.null(opt$mostIntense)){
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34 mostIntense = FALSE
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35 }else{
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36 mostIntense = TRUE
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37 }
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38
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39 if(is.null(opt$convert2RawRT)){
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40 convert2RawRT = FALSE
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41 }else{
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42 convert2RawRT= TRUE
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43 }
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45 # Makes sure the same files are being used
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46 if(!all(basename(pa@fileList)==basename(xset@filepaths))){
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47 if(!all(names(pa@fileList)==basename(xset@filepaths))){
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48 quit(status = 1)
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49 }else{
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50 xset@filepaths <- unname(pa@fileList)
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51 }
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52 }
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53
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54 if (!is.null(opt$mzML_files) && !is.null(opt$galaxy_names)){
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55 # NOTE: This only works if the pa file was generated IN Galaxy!! Relies on
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56 # the pa@fileList having the names of files given as 'names' of the variables (done in frag4feature)
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57 # Will update in the next version of msPurity
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58 filepaths <- trimws(strsplit(opt$mzML_files, ',')[[1]])
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59 filepaths <- filepaths[filepaths != ""]
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60 new_names <- basename(filepaths)
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61
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62 galaxy_names <- trimws(strsplit(opt$galaxy_names, ',')[[1]])
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63 galaxy_names <- galaxy_names[galaxy_names != ""]
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64
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65 nsave <- names(pa@fileList)
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66 old_filenames <- basename(pa@fileList)
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67 pa@fileList <- filepaths[match(names(pa@fileList), galaxy_names)]
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68
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69 pa@puritydf$filename <- basename(pa@fileList[match(pa@puritydf$filename, old_filenames)])
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70 pa@grped_df$filename <- basename(pa@fileList[match(pa@grped_df$filename, old_filenames)])
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71 }
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72
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73 if(!all(basename(pa@fileList)==basename(xset@filepaths))){
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74 if(!all(names(pa@fileList)==basename(xset@filepaths))){
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75 quit(status = 1)
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76 }else{
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77 xset@filepaths <- unname(pa@fileList)
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78 }
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79 }
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80
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81 if(is.null(opt$grp_peaklist)){
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82 grp_peaklist = NA
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83 }else{
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84 grp_peaklist = opt$grp_peaklist
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85 }
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86
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87 print(pa)
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88 print(pa@fileList)
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89 print(xset)
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90 print(xset@filepaths)
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91 print(opt$ppm)
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92 print(opt$plim)
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93 print(convert2RawRT)
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94
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98 pa <- msPurity::frag4feature(pa=pa, xset=xset, ppm=opt$ppm, plim=opt$plim,
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99 intense=opt$mostIntense, convert2RawRT=convert2RawRT,
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100 db_name='alldata.sqlite', out_dir=opt$out_dir, grp_peaklist=grp_peaklist)
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102 save(pa, file=file.path(opt$out_dir, 'frag4feature.RData'))
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104 print(head(pa@grped_df))
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105 write.table(pa@grped_df, file.path(opt$out_dir, 'frag4feature.tsv'), row.names=FALSE, sep='\t')