Mercurial > repos > prog > lcmsmatching

annotate biodb-common.R @ 7:882f2f20028b draft

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planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit 608d9e59a0d2dcf85a037968ddb2c61137fb9bce
author prog
date Sun, 09 Apr 2017 10:44:21 -0400
parents 45e985cd8e9e
children
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45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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1 if ( ! exists('BIODB.XML')) {
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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3 ###############
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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4 # CACHE MODES #
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5 ###############
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45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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7 BIODB.CACHE.READ.ONLY <- 'read-only'
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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8 BIODB.CACHE.READ.WRITE <- 'read-write'
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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9 BIODB.CACHE.WRITE.ONLY <- 'write-only'
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45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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11 #######################
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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12 # ENTRY CONTENT TYPES #
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13 #######################
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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15 BIODB.HTML <- 'html'
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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16 BIODB.TXT <- 'txt'
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17 BIODB.XML <- 'xml'
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18 BIODB.CSV <- 'csv'
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19 BIODB.DATAFRAME <- 'dataframe'
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20 BIODB.JSON <- 'json'
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3afe41d3e9e7 planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit bb4d3e23d99828bfee16d31d794c49a17313ec2f
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22 #############
1
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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23 # DATABASES #
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24 #############
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1
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26 BIODB.CHEBI <- 'chebi'
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27 BIODB.KEGG <- 'kegg'
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28 BIODB.PUBCHEMCOMP <- 'pubchemcomp' # Compound database
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29 BIODB.PUBCHEMSUB <- 'pubchemsub' # Substance database
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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30 BIODB.HMDB <- 'hmdb'
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31 BIODB.CHEMSPIDER <- 'chemspider'
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32 BIODB.ENZYME <- 'enzyme'
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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33 BIODB.LIPIDMAPS <- 'lipidmaps'
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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34 BIODB.MIRBASE <- 'mirbase'
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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35 BIODB.NCBIGENE <- 'ncbigene'
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36 BIODB.NCBICCDS <- 'ncbiccds'
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37 BIODB.UNIPROT <- 'uniprot'
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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38 BIODB.MASSBANK <- 'massbank'
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39 BIODB.MASSFILEDB <- 'massfiledb'
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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40 BIODB.PEAKFOREST <- 'peakforest'
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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42 BIODB.DATABASES <- c(BIODB.CHEBI, BIODB.KEGG, BIODB.PUBCHEMCOMP, BIODB.PUBCHEMSUB, BIODB.HMDB, BIODB.CHEMSPIDER, BIODB.ENZYME, BIODB.LIPIDMAPS, BIODB.MIRBASE, BIODB.NCBIGENE, BIODB.NCBICCDS, BIODB.UNIPROT, BIODB.MASSBANK, BIODB.MASSFILEDB, BIODB.PEAKFOREST)
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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44 ##########
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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45 # FIELDS #
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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46 ##########
0
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47
1
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48 BIODB.ACCESSION <- 'accession'
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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49 BIODB.DESCRIPTION <- 'description'
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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50 BIODB.PROTEIN.DESCRIPTION <- 'protdesc'
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51 BIODB.NAME <- 'name'
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52 BIODB.COMP.IUPAC.NAME.ALLOWED <- 'comp.iupac.name.allowed'
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53 BIODB.COMP.IUPAC.NAME.TRAD <- 'comp.iupac.name.trad'
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54 BIODB.COMP.IUPAC.NAME.SYST <- 'comp.iupac.name.syst'
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55 BIODB.COMP.IUPAC.NAME.PREF <- 'comp.iupac.name.pref'
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56 BIODB.COMP.IUPAC.NAME.CAS <- 'comp.iupac.name.cas'
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57 BIODB.FULLNAMES <- 'fullnames'
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58 BIODB.SYNONYMS <- 'synonyms'
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59 BIODB.SYMBOL <- 'symbol'
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60 BIODB.GENE.SYMBOLS <- 'genesymbols'
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61 BIODB.CHEBI.ID <- 'chebiid'
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62 BIODB.LIPIDMAPS.ID <- 'lipidmapsid'
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63 BIODB.KEGG.ID <- 'keggid'
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64 BIODB.HMDB.ID <- 'hmdbid'
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65 BIODB.ENZYME.ID <- 'enzymeid'
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66 BIODB.NCBI.CCDS.ID <- 'ncbiccdsid'
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67 BIODB.NCBI.GENE.ID <- 'ncbigeneid'
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68 BIODB.PUBCHEMCOMP.ID <- 'pubchemcompid'
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69 BIODB.PUBCHEMSUB.ID <- 'pubchemsubid'
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70 BIODB.CHEMSPIDER.ID <- 'chemspiderid'
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71 BIODB.UNIPROT.ID <- 'uniprotid'
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72 BIODB.CAS.ID <- 'casid'
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73 BIODB.PEAKFOREST.ID <- 'peakforestid'
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74 BIODB.SMILES <- 'smiles'
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75 BIODB.INCHI <- 'inchi'
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76 BIODB.INCHIKEY <- 'inchikey'
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77 BIODB.MSDEV <- 'msdev'
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78 BIODB.MSDEVTYPE <- 'msdevtype'
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79 BIODB.MSTYPE <- 'mstype'
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80 BIODB.MSMODE <- 'msmode'
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81 BIODB.MSPRECMZ <- 'msprecmz' # numeric
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82 BIODB.MSPRECANNOT <- 'msprecannot'
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83 BIODB.FORMULA <- 'formula'
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84 BIODB.SUPER.CLASS <- 'superclass'
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85 BIODB.MASS <- 'mass'
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86 BIODB.AVERAGE.MASS <- 'averagemass'
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87 BIODB.MONOISOTOPIC.MASS <- 'monoisotopicmass'
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88 BIODB.SEQUENCE <- 'sequence'
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89 BIODB.LOCATION <- 'location'
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90 BIODB.LENGTH <- 'length'
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91 BIODB.NB.PEAKS <- 'nbpeaks'
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92 BIODB.PEAKS <- 'peaks'
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93 BIODB.COMPOUNDS <- 'compounds'
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94 BIODB.NB.COMPOUNDS <- 'nbcompounds'
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95 BIODB.COMPOUND.ID <- 'compoundid'
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96 BIODB.COMPOUND.MASS <- 'compoundmass'
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97 BIODB.COMPOUND.COMP <- 'compoundcomp'
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98 BIODB.CHROM.COL <- 'chromcol' # Chromatographic column
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99 BIODB.CHROM.COL.RT <- 'chromcolrt' # Retention time measured on chromatographic column
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100 BIODB.ID <- 'id'
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101 BIODB.TITLE <- 'title'
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102 BIODB.PEAK.MZ <- 'mz'
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103 BIODB.PEAK.RT <- 'rt'
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104 BIODB.PEAK.MZEXP <- 'mzexp'
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105 BIODB.PEAK.MZTHEO <- 'mztheo'
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106 BIODB.PEAK.FORMULA <- 'formula'
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107 BIODB.PEAK.FORMULA.COUNT <- 'formula.count'
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108 BIODB.PEAK.COMP <- 'peakcomp' # Peak composition
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109 BIODB.PEAK.ATTR <- 'peakattr' # Peak attribution
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110 BIODB.PEAK.MASS <- 'mass'
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111 # BIODB.PEAK.ATTR <- 'attr'
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112 BIODB.PEAK.ERROR.PPM <- 'error.ppm'
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113 BIODB.PEAK.INTENSITY <- 'intensity'
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114 BIODB.PEAK.RELATIVE.INTENSITY <- 'relative.intensity'
0
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115
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116 # Mode values
1
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117 BIODB.MSMODE.NEG <- 'neg'
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118 BIODB.MSMODE.POS <- 'pos'
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119
1
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120 # Tolerance values
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121 BIODB.TOL <- 'mztol'
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122 BIODB.MZTOLUNIT.PPM <- 'ppm'
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123 BIODB.MZTOLUNIT.PLAIN <- 'plain' # same as mz: mass-to-charge ratio
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124 BIODB.MZTOLUNIT.VALS <- c(BIODB.MZTOLUNIT.PPM, BIODB.MZTOLUNIT.PLAIN)
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125
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126 ########################
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127 # MS-MS MEASURE VALUES #
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128 ########################
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129
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130 BIODB.MSMS.DIST.COS <- "cosine"
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131 BIODB.MSMS.DIST.WCOSINE <- "wcosine"
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132 BIODB.MSMS.DIST.PKERNEL <- "pkernel"
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133 BIODB.MSMS.DIST <- c(BIODB.MSMS.DIST.COS, BIODB.MSMS.DIST.WCOSINE, BIODB.MSMS.DIST.PKERNEL)
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134
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135
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136 #################
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137 # CARDINALITIES #
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138 #################
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139
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140 BIODB.CARD.ONE <- '1'
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141 BIODB.CARD.MANY <- '*'
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142
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143 #####################
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144 #INTENSITy NOTATIONS#
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145 #####################
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146
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147 BIODB.GROUP.INTENSITY<-c(BIODB.PEAK.INTENSITY,BIODB.PEAK.RELATIVE.INTENSITY)
0
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148
1
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149 ##########################
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150 # ENTRY FIELD ATTRIBUTES #
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151 ##########################
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152 # FIELD NAME CLASS CARDINALITY TYPE
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153 BIODB.FIELDS <- data.frame(matrix(c(
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154 BIODB.ACCESSION, 'character', BIODB.CARD.ONE, 'none',
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155 BIODB.DESCRIPTION, 'character', BIODB.CARD.ONE, 'none',
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156 BIODB.NAME, 'character', BIODB.CARD.ONE, 'name',
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157 BIODB.COMP.IUPAC.NAME.ALLOWED, 'character', BIODB.CARD.ONE, 'name',
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158 BIODB.COMP.IUPAC.NAME.TRAD, 'character', BIODB.CARD.ONE, 'name',
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159 BIODB.COMP.IUPAC.NAME.SYST, 'character', BIODB.CARD.ONE, 'name',
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160 BIODB.COMP.IUPAC.NAME.PREF, 'character', BIODB.CARD.ONE, 'name',
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161 BIODB.COMP.IUPAC.NAME.CAS, 'character', BIODB.CARD.ONE, 'name',
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162 BIODB.FULLNAMES, 'character', BIODB.CARD.MANY, 'name',
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163 BIODB.SYNONYMS, 'character', BIODB.CARD.MANY, 'name',
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164 BIODB.PROTEIN.DESCRIPTION, 'character', BIODB.CARD.ONE, 'none',
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165 BIODB.SYMBOL, 'character', BIODB.CARD.ONE, 'none',
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166 BIODB.GENE.SYMBOLS, 'character', BIODB.CARD.MANY, 'none',
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167 BIODB.NB.COMPOUNDS, 'integer', BIODB.CARD.ONE, 'none',
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168 BIODB.COMPOUNDS, 'object', BIODB.CARD.MANY, 'none',
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169 BIODB.CHEBI.ID, 'character', BIODB.CARD.ONE, 'none',
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170 BIODB.LIPIDMAPS.ID, 'character', BIODB.CARD.ONE, 'none',
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171 BIODB.KEGG.ID, 'character', BIODB.CARD.ONE, 'none',
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172 BIODB.HMDB.ID, 'character', BIODB.CARD.ONE, 'none',
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173 BIODB.ENZYME.ID, 'character', BIODB.CARD.ONE, 'none',
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174 BIODB.PUBCHEMCOMP.ID, 'character', BIODB.CARD.ONE, 'none',
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175 BIODB.PUBCHEMSUB.ID, 'character', BIODB.CARD.ONE, 'none',
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176 BIODB.PEAKFOREST.ID, 'character', BIODB.CARD.ONE, 'none',
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177 BIODB.UNIPROT.ID, 'character', BIODB.CARD.ONE, 'none',
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178 BIODB.NCBI.CCDS.ID, 'character', BIODB.CARD.ONE, 'none',
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179 BIODB.NCBI.GENE.ID, 'character', BIODB.CARD.ONE, 'none',
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180 BIODB.INCHI, 'character', BIODB.CARD.ONE, 'none',
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181 BIODB.INCHIKEY, 'character', BIODB.CARD.ONE, 'none',
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182 BIODB.MSDEV, 'character', BIODB.CARD.ONE, 'none',
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183 BIODB.MSDEVTYPE, 'character', BIODB.CARD.ONE, 'none',
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184 BIODB.MSTYPE, 'character', BIODB.CARD.ONE, 'none',
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185 BIODB.MSMODE, 'character', BIODB.CARD.ONE, 'none',
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186 BIODB.MSPRECMZ, 'double', BIODB.CARD.ONE, 'none',
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187 BIODB.PEAK.MZTHEO, 'double', BIODB.CARD.ONE, 'none',
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188 BIODB.MSPRECANNOT, 'character', BIODB.CARD.ONE, 'none',
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189 BIODB.FORMULA, 'character', BIODB.CARD.ONE, 'none',
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190 BIODB.SUPER.CLASS, 'character', BIODB.CARD.ONE, 'none',
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191 BIODB.MASS, 'double', BIODB.CARD.ONE, 'none',
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192 BIODB.AVERAGE.MASS, 'double', BIODB.CARD.ONE, 'none',
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193 BIODB.MONOISOTOPIC.MASS, 'double', BIODB.CARD.ONE, 'none',
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194 BIODB.SEQUENCE, 'character', BIODB.CARD.ONE, 'none',
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195 BIODB.LENGTH, 'integer', BIODB.CARD.ONE, 'none',
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196 BIODB.LOCATION, 'character', BIODB.CARD.ONE, 'none',
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197 BIODB.NB.PEAKS, 'integer', BIODB.CARD.ONE, 'none',
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198 BIODB.PEAKS, 'data.frame', BIODB.CARD.ONE, 'none',
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199 BIODB.SMILES, 'character', BIODB.CARD.ONE, 'none',
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200 BIODB.CHEMSPIDER.ID, 'character', BIODB.CARD.ONE, 'none',
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201 BIODB.CAS.ID, 'character', BIODB.CARD.ONE, 'none'
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202 ), byrow = TRUE, ncol = 4), stringsAsFactors = FALSE)
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203 colnames(BIODB.FIELDS) <- c('name', 'class', 'cardinality', 'type')
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204
1
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205 #########################
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206 # GET DATABASE ID FIELD #
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207 #########################
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208
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209 biodb.get.database.id.field <- function(database) {
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210
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211 id.field <- NA_character_
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212
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213 if (database %in% BIODB.DATABASES) {
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214 id.field <- paste0(database, 'id')
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215 if ( ! id.field %in% BIODB.FIELDS[['name']])
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216 stop(paste0('No ID field defined for database ', database, '.'))
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217 }
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218
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219 return(id.field)
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220 }
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221
1
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222 #####################
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223 # COMPUTABLE FIELDS #
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224 #####################
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225
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226 BIODB.FIELD.COMPUTING <- list()
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227 BIODB.FIELD.COMPUTING[[BIODB.INCHI]] <- c(BIODB.CHEBI)
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228 BIODB.FIELD.COMPUTING[[BIODB.INCHIKEY]] <- c(BIODB.CHEBI)
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229 BIODB.FIELD.COMPUTING[[BIODB.SEQUENCE]] <- c(BIODB.NCBICCDS)
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230
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231 ####################
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232 # PEAKS DATA FRAME #
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233 ####################
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234
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235 # Example
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236 BIODB.PEAK.DF.EXAMPLE <- data.frame(mz = double(), int = double(), rel.int = integer(), formula = character(), formula.count <- integer(), mass = double(), error = double(), stringsAsFactors = FALSE)
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237 colnames(BIODB.PEAK.DF.EXAMPLE) <- c(BIODB.PEAK.MZ, BIODB.PEAK.INTENSITY, BIODB.PEAK.RELATIVE.INTENSITY, BIODB.PEAK.FORMULA, BIODB.PEAK.FORMULA.COUNT, BIODB.PEAK.MASS, BIODB.PEAK.ERROR.PPM)
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238
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239 #################
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240 # GET ENTRY URL #
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241 #################
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242
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243 # TODO Let the choice to use either jp or eu
1
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244 BIODB.MASSBANK.JP.WS.URL <- "http://www.massbank.jp/api/services/MassBankAPI/"
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245 BIODB.MASSBANK.EU.WS.URL <- "http://massbank.eu/api/services/MassBankAPI/"
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246
1
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247 .do.get.entry.url <- function(class, accession, content.type = BIODB.HTML, base.url = NA_character_, token = NA_character_) {
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248
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249 # Only certain databases can handle multiple accession ids
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250 if ( ! class %in% c(BIODB.MASSBANK, BIODB.CHEMSPIDER, BIODB.PUBCHEMCOMP, BIODB.PUBCHEMSUB, BIODB.PEAKFOREST) && length(accession) > 1)
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251 stop(paste0("Cannot build a URL for getting multiple entries for class ", class, "."))
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252
1
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253 # Get URL
0
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254 url <- switch(class,
1
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255 chebi = if (content.type == BIODB.HTML) paste0('https://www.ebi.ac.uk/chebi/searchId.do?chebiId=', accession) else NULL,
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256 chemspider = {
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257 token.param <- if (is.na(token)) '' else paste('&token', token, sep = '=')
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258 switch(content.type,
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259 html = paste0('http://www.chemspider.com/Chemical-Structure.', accession, '.html'),
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260 xml = paste0('http://www.chemspider.com/MassSpecAPI.asmx/GetExtendedCompoundInfoArray?', paste(paste0('CSIDs=', accession), collapse = '&'), token.param),
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261 NULL)
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262 },
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263 enzyme = if (content.type == BIODB.TXT) paste0('http://enzyme.expasy.org/EC/', accession, '.txt') else NULL,
0
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264 hmdb = switch(content.type,
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265 xml = paste0('http://www.hmdb.ca/metabolites/', accession, '.xml'),
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266 html = paste0('http://www.hmdb.ca/metabolites/', accession),
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267 NULL),
3afe41d3e9e7 planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit bb4d3e23d99828bfee16d31d794c49a17313ec2f
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268 kegg = switch(content.type,
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269 txt = paste0('http://rest.kegg.jp/get/', accession),
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270 html = paste0('http://www.genome.jp/dbget-bin/www_bget?cpd:', accession),
1
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271 NULL),
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272 lipidmaps = if (content.type == BIODB.CSV) paste0('http://www.lipidmaps.org/data/LMSDRecord.php?Mode=File&LMID=', accession, '&OutputType=CSV&OutputQuote=No') else NULL,
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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273 massbank = if (content.type == BIODB.TXT) paste0((if (is.na(base.url)) BIODB.MASSBANK.EU.WS.URL else base.url), 'getRecordInfo?ids=', paste(accession, collapse = ',')) else NULL,
45e985cd8e9e planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty
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274 mirbase = if (content.type == BIODB.HTML) paste0('http://www.mirbase.org/cgi-bin/mature.pl?mature_acc=', accession) else NULL,
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275 pubchemcomp = switch(content.type,
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276 xml = paste0('https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/cid/', paste(accession, collapse = ','), '/XML'),
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277 html = paste0('http://pubchem.ncbi.nlm.nih.gov/compound/', accession),
0
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278 NULL),
1
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279 pubchemsub = switch(content.type,
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280 xml = paste0('https://pubchem.ncbi.nlm.nih.gov/rest/pug/substance/sid/', paste(accession, collapse = ','), '/XML'),
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281 html = paste0('http://pubchem.ncbi.nlm.nih.gov/substance/', accession),
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282 NULL),
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283 ncbigene = if (content.type == BIODB.XML) paste0('https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=gene&id=', accession, '&rettype=xml&retmode=text') else NULL,
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284 ncbiccds = if (content.type == BIODB.HTML) paste0('https://www.ncbi.nlm.nih.gov/CCDS/CcdsBrowse.cgi?REQUEST=CCDS&GO=MainBrowse&DATA=', accession),
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285 uniprot = if (content.type == BIODB.XML) paste0('http://www.uniprot.org/uniprot/', accession, '.xml'),
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286 peakforest = switch(content.type,
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287 html= paste0('https://peakforest.org/home?PFs=',accession),
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288 json= paste0('https://peakforest-alpha.inra.fr/rest/spectra/lcms/ids/',paste(accession,sep=','),'?token=',token),
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289
0
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290 NULL
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291 )
1
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292 )
0
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293 return(url)
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294 }
1
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295
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296 get.entry.url <- function(class, accession, content.type = BIODB.HTML, max.length = 0, base.url = NA_character_, token = NA_character_) {
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297
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298 if (length(accession) == 0)
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299 return(NULL)
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300
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301 full.url <- .do.get.entry.url(class, accession, content.type = content.type, base.url = base.url, token = token)
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302 if (max.length == 0 || nchar(full.url) <= max.length)
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303 return(if (max.length == 0) full.url else list(url = full.url, n = length(accession)))
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304
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305 # Find max size URL
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306 a <- 1
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307 b <- length(accession)
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308 while (a < b) {
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309 m <- as.integer((a + b) / 2)
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310 url <- .do.get.entry.url(class, accession[1:m], content.type = content.type, base.url = base.url, token = token)
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311 if (nchar(url) <= max.length && m != a)
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312 a <- m
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313 else
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314 b <- m
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315 }
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316 url <- .do.get.entry.url(class, accession[1:a], content.type = content.type, base.url = base.url, token = token)
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317
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318 return(list( url = url, n = a))
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319 }
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320
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321 #################
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322 # PRINT MESSAGE #
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323 #################
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324
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325 BIODB.DEBUG <- 1
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326 BIODB.LEVEL.NAMES <- c('DEBUG')
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327
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328 .print.msg <- function(msg, level = BIODB.DEBUG, class = NA_character_) {
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329 cat(paste0(BIODB.LEVEL.NAMES[[level]], if (is.na(class)) '' else paste0(", ", class), ": ", msg, "\n"), file = stderr())
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330 }
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331
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332 #####################
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333 # BIODB GET ENV VAR #
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334 #####################
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335
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336 .biodb.get.env.var <- function(v) {
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337
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338 # Get all env vars
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339 env <- Sys.getenv()
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340
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341 # Make env var name
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342 env.var <- paste(c('BIODB', toupper(v)), collapse = '_')
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343
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344 # Look if this env var exists
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345 if (env.var %in% names(env))
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346 return(env[[env.var]])
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347
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348 return(NA_character_)
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349 }
0
3afe41d3e9e7 planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit bb4d3e23d99828bfee16d31d794c49a17313ec2f
prog
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