METAbolic pathway testing combining POsitive and NEgative mode data (metapone)

The metapone package conducts pathway tests for untargeted metabolomics data. It has three main characteristics: (1) expanded database combining SMPDB and Mummichog databases, with manual cleaning to remove redundancies; (2) A new weighted testing scheme to address the issue of metabolite-feature matching uncertainties; (3) Can consider positive mode and negative mode data in a single analysis.

Compared to existing methods, the weighted testing scheme allows the user to apply different level of penalty for multiple-mapped features, in order to reduce their undue impact on the results. In addition, considering positive mode and negative mode data simultaneously can improve the statistical power of the test.

library(metapone)
#> Loading required package: BiocParallel
#> Loading required package: fields
#> Loading required package: spam
#> Loading required package: dotCall64
#> Loading required package: grid
#> Spam version 2.7-0 (2021-06-25) is loaded.
#> Type 'help( Spam)' or 'demo( spam)' for a short introduction 
#> and overview of this package.
#> Help for individual functions is also obtained by adding the
#> suffix '.spam' to the function name, e.g. 'help( chol.spam)'.
#> 
#> Attaching package: 'spam'
#> The following objects are masked from 'package:base':
#> 
#>     backsolve, forwardsolve
#> Loading required package: viridis
#> Loading required package: viridisLite
#> See https://github.com/NCAR/Fields for
#>  an extensive vignette, other supplements and source code
#> Loading required package: markdown
#> 
#> Attaching package: 'metapone'
#> The following object is masked from 'package:stats':
#> 
#>     ftable

The input should contain at least three clumns - m/z, retention time, and feature p-value. Here to illustrate the usage of the method, we borrow the test results from our published study “Use of high-resolution metabolomics for the identification of metabolic T signals associated with traffic-related air pollution” in Environment International. 120: 145–154.

The positive mode results are in the object “pos”.

data(pos)
head(pos)
#>        m.z retention.time    p.value statistic
#> 1 85.04027       55.66454 0.22109229 -1.231240
#> 2 85.07662       56.93586 0.52181695 -0.642790
#> 3 85.57425      125.97117 0.13483680 -1.507372
#> 4 86.06064      194.81306 0.26069118  1.131101
#> 5 86.08001       54.74512 0.17206535  1.375352
#> 6 86.09704      177.73650 0.07541608  1.796427

The negative mode results are in the object “neg”. If both positive mode and negative mode data are present, each is input into the algorithm as a separate matrix

data(neg)
head(neg)
#>                mz       chr      pval t-statistic
#> result.1 85.00448 268.83027 0.2423777   1.1690645
#> result.2 87.00881  48.84882 0.2222984   1.2204394
#> result.3 87.92531 161.99560 0.1341622   1.4978887
#> result.4 88.00399 129.88520 0.2941855  -1.0489839
#> result.5 88.01216  35.81698 0.8510984  -0.1877171
#> result.6 88.98808 127.47973 0.1748255  -1.3568608

It is not required that both positive and negative mode results are present. Having a single ion mode is also OK. The test is based on HMDB identification. The common adduct ions are pre-processed and stored in:

data(hmdbCompMZ)
head(hmdbCompMZ)
#>       HMDB_ID      m.z ion.type
#> 1 HMDB0059597 1.343218     M+3H
#> 2 HMDB0001362 1.679159     M+3H
#> 3 HMDB0037238 2.341477     M+3H
#> 4 HMDB0005949 3.345944     M+3H
#> 5 HMDB0002387 4.011337     M+3H
#> 6 HMDB0002386 4.677044     M+3H

Pathway information that was summarized from Mummichog and smpdb is built-in:

data(pa)
head(pa)
#>       database         pathway.name     HMDB.ID KEGG.ID  category
#> 1 Metapone 191 Pterine Biosynthesis HMDB0006822  C05922 Metabolic
#> 2 Metapone 191 Pterine Biosynthesis HMDB0002111  C00001 Metabolic
#> 3 Metapone 191 Pterine Biosynthesis HMDB0006821  C05923 Metabolic
#> 4 Metapone 191 Pterine Biosynthesis HMDB0000142  C00058 Metabolic
#> 5 Metapone 191 Pterine Biosynthesis HMDB0015532         Metabolic
#> 6 Metapone 191 Pterine Biosynthesis HMDB0001273  C00044 Metabolic

The user can specify which adduct ions are allowed by setting the allowed adducts. For example:

pos.adductlist = c("M+H", "M+NH4", "M+Na", "M+ACN+H", "M+ACN+Na", "M+2ACN+H", "2M+H", "2M+Na", "2M+ACN+H")
neg.adductlist = c("M-H", "M-2H", "M-2H+Na", "M-2H+K", "M-2H+NH4", "M-H2O-H", "M-H+Cl", "M+Cl", "M+2Cl")

It is common for a feature to be matched to multiple metabolites. Assume a feature is matched to m metabolites, metapone weighs the feature by (1/m)^p, where p is a power term to tune the penalty. m can also be capped at a certain level such that the penalty is limited. These are controlled by parameters:

Setting p: fractional.count.power = 0.5 Setting the cap of n: max.match.count = 10

It is easy to see that when p=0, no penalty is assigned for multiple-matching. The higher p is, the larger penalty for features that are multiple matched.

Other parameters include p.threshold, which controls which metabolic feature is considered significant. The testing is done by permutation. Overall, the analysis is conducted this way:

r<-metapone(pos, neg, pa, hmdbCompMZ=hmdbCompMZ, pos.adductlist=pos.adductlist, neg.adductlist=neg.adductlist, p.threshold=0.05,n.permu=100,fractional.count.power=0.5, max.match.count=10)
hist(ptable(r)[,1])

We can subset the pathways that are significant:

selection<-which(ptable(r)[,1]<0.025)
ptable(r)[selection,]
#>                                                             p_value
#> Glycosphingolipid metabolism                                   0.00
#> C21-steroid hormone biosynthesis and metabolism                0.02
#> Porphyrin Metabolism                                           0.01
#> Purine Metabolism                                              0.00
#> Sphingolipid Metabolism                                        0.00
#> FoxO signaling pathway                                         0.02
#> Fatty acid degradation                                         0.01
#> Glycine, serine and threonine metabolism                       0.02
#> Protein digestion and absorption                               0.01
#> Biosynthesis of alkaloids derived from histidine and purine    0.02
#> Valine, leucine and isoleucine degradation                     0.02
#> Porphyrin and chlorophyll metabolism                           0.02
#> Sphingolipid metabolism                                        0.02
#> Estrogen signaling pathway                                     0.00
#> One carbon pool by folate                                      0.00
#>                                                             n_significant metabolites
#> Glycosphingolipid metabolism                                                2.8395164
#> C21-steroid hormone biosynthesis and metabolism                             4.8363062
#> Porphyrin Metabolism                                                        3.1213203
#> Purine Metabolism                                                           4.6733053
#> Sphingolipid Metabolism                                                     2.8395164
#> FoxO signaling pathway                                                      0.4007921
#> Fatty acid degradation                                                      0.8779645
#> Glycine, serine and threonine metabolism                                    3.0031471
#> Protein digestion and absorption                                            3.4768951
#> Biosynthesis of alkaloids derived from histidine and purine                 2.1674622
#> Valine, leucine and isoleucine degradation                                  2.0615286
#> Porphyrin and chlorophyll metabolism                                        1.8506493
#> Sphingolipid metabolism                                                     1.9743680
#> Estrogen signaling pathway                                                  0.2085144
#> One carbon pool by folate                                                   0.8944272
#>                                                             n_mapped_metabolites
#> Glycosphingolipid metabolism                                          13.9627029
#> C21-steroid hormone biosynthesis and metabolism                       28.3710206
#> Porphyrin Metabolism                                                  12.8947329
#> Purine Metabolism                                                     31.7643456
#> Sphingolipid Metabolism                                               15.1783390
#> FoxO signaling pathway                                                 1.9297107
#> Fatty acid degradation                                                 4.6048231
#> Glycine, serine and threonine metabolism                              20.3647444
#> Protein digestion and absorption                                      26.7442719
#> Biosynthesis of alkaloids derived from histidine and purine           15.5190000
#> Valine, leucine and isoleucine degradation                             9.1648402
#> Porphyrin and chlorophyll metabolism                                   8.2950505
#> Sphingolipid metabolism                                                8.1798097
#> Estrogen signaling pathway                                             0.2085144
#> One carbon pool by folate                                              0.8944272
#>                                                             n_metabolites
#> Glycosphingolipid metabolism                                           45
#> C21-steroid hormone biosynthesis and metabolism                        80
#> Porphyrin Metabolism                                                   47
#> Purine Metabolism                                                      91
#> Sphingolipid Metabolism                                                40
#> FoxO signaling pathway                                                  5
#> Fatty acid degradation                                                 40
#> Glycine, serine and threonine metabolism                               41
#> Protein digestion and absorption                                       43
#> Biosynthesis of alkaloids derived from histidine and purine            32
#> Valine, leucine and isoleucine degradation                             33
#> Porphyrin and chlorophyll metabolism                                   40
#> Sphingolipid metabolism                                                19
#> Estrogen signaling pathway                                              8
#> One carbon pool by folate                                               9
#>                                                             significant metabolites
#> Glycosphingolipid metabolism                                                   <NA>
#> C21-steroid hormone biosynthesis and metabolism                                <NA>
#> Porphyrin Metabolism                                                           <NA>
#> Purine Metabolism                                                              <NA>
#> Sphingolipid Metabolism                                                        <NA>
#> FoxO signaling pathway                                                         <NA>
#> Fatty acid degradation                                                         <NA>
#> Glycine, serine and threonine metabolism                                       <NA>
#> Protein digestion and absorption                                               <NA>
#> Biosynthesis of alkaloids derived from histidine and purine                    <NA>
#> Valine, leucine and isoleucine degradation                                     <NA>
#> Porphyrin and chlorophyll metabolism                                           <NA>
#> Sphingolipid metabolism                                                        <NA>
#> Estrogen signaling pathway                                                     <NA>
#> One carbon pool by folate                                                      <NA>
#>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              mapped_metabolites
#> Glycosphingolipid metabolism                                                                                                                                                                                                                                                                                                                                                                    HMDB0001565,HMDB0000224,HMDB0000220,HMDB0000252,HMDB0001383,HMDB0001551,HMDB0000277,HMDB0003449,HMDB0001480,HMDB0000122,HMDB0000187,HMDB0006752,HMDB0004866,HMDB0000648,HMDB0001448,HMDB0006591
#> C21-steroid hormone biosynthesis and metabolism             HMDB0000653,HMDB0006759,HMDB0004026,HMDB0006762,HMDB0000015,HMDB0011653,HMDB0004031,HMDB0004030,HMDB0000016,HMDB0004029,HMDB0006758,HMDB0000319,HMDB0000949,HMDB0000268,HMDB0006755,HMDB0006278,HMDB0000990,HMDB0002833,HMDB0006281,HMDB0060512,HMDB0002829,HMDB0001231,HMDB0006756,HMDB0006203,HMDB0006280,HMDB0001032,HMDB0000774,HMDB0001318,HMDB0000374,HMDB0006763,HMDB0006224,HMDB0004484,HMDB0000374,HMDB0000253,HMDB0001547,HMDB0000142,HMDB0001448,HMDB0003193,HMDB0000042,HMDB0000363,HMDB0003069,HMDB0000063,HMDB0006773
#> Porphyrin Metabolism                                                                                                                                                                                                                                                                                                                                                                                        HMDB0000123,HMDB0001149,HMDB0000245,HMDB0002111,HMDB0002158,HMDB0001261,HMDB0001377,HMDB0003125,HMDB0000692,HMDB0001008,HMDB0000054,HMDB0003325,HMDB0060273,HMDB0000127,HMDB0001264
#> Purine Metabolism                                                                                                                               HMDB0002111,HMDB0001429,HMDB0000085,HMDB0000132,HMDB0000292,HMDB0000148,HMDB0000641,HMDB0000123,HMDB0000972,HMDB0001235,HMDB0000191,HMDB0000134,HMDB0001517,HMDB0000175,HMDB0000299,HMDB0000195,HMDB0000157,HMDB0001377,HMDB0003125,HMDB0000289,HMDB0000071,HMDB0000050,HMDB0000034,HMDB0011629,HMDB0003335,HMDB0001314,HMDB0000044,HMDB0000283,HMDB0030097,HMDB0003537,HMDB0000293,HMDB0000462,HMDB0006555,HMDB0001005,HMDB0000294,HMDB0000243
#> Sphingolipid Metabolism                                                                                                                                                                                                                                                                                                                                                                                     HMDB0000187,HMDB0001480,HMDB0001383,HMDB0002111,HMDB0001429,HMDB0000224,HMDB0001551,HMDB0006752,HMDB0000277,HMDB0000252,HMDB0001565,HMDB0000122,HMDB0004866,HMDB0001448,HMDB0000143
#> FoxO signaling pathway                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  HMDB0000148,HMDB0000122
#> Fatty acid degradation                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  HMDB0000220,HMDB0000661,HMDB0001551,HMDB0003424,HMDB0000222,HMDB0000115
#> Glycine, serine and threonine metabolism                                                                                                                                                                                                                    HMDB0000243,HMDB0000123,HMDB0000119,HMDB0000191,HMDB0000187,HMDB0000929,HMDB0000005,HMDB0001352,HMDB0000167,HMDB0060180,HMDB0000271,HMDB0000139,HMDB0000719,HMDB0000064,HMDB0001149,HMDB0012249,HMDB0001167,HMDB0003391,HMDB0000043,HMDB0003406,HMDB0000092,HMDB0002134,HMDB0010163,HMDB0006284,HMDB0006454,HMDB0004041,HMDB0031411
#> Protein digestion and absorption                                                                                                                                                    HMDB0000148,HMDB0000042,HMDB0000123,HMDB0000161,HMDB0000182,HMDB0000191,HMDB0000517,HMDB0000641,HMDB0000187,HMDB0000696,HMDB0000929,HMDB0000159,HMDB0000158,HMDB0000056,HMDB0000687,HMDB0000177,HMDB0000162,HMDB0000168,HMDB0000237,HMDB0000883,HMDB0000167,HMDB0000039,HMDB0000870,HMDB0000172,HMDB0000738,HMDB0000306,HMDB0000192,HMDB0000588,HMDB0001858,HMDB0034301,HMDB0001873,HMDB0000718,HMDB0002176
#> Biosynthesis of alkaloids derived from histidine and purine                                                                                                                                                                                                                                                                         HMDB0000243,HMDB0000208,HMDB0000254,HMDB0000134,HMDB0000687,HMDB0000175,HMDB0000177,HMDB0000156,HMDB0000094,HMDB0060180,HMDB0003345,HMDB0000193,HMDB0000292,HMDB0000870,HMDB0000072,HMDB0000299,HMDB0001517,HMDB0001889,HMDB0002825,HMDB0001847,HMDB0000718
#> Valine, leucine and isoleucine degradation                                                                                                                                                                                                                                                                                                                                                                                                      HMDB0000687,HMDB0000019,HMDB0000060,HMDB0000883,HMDB0000695,HMDB0001172,HMDB0000172,HMDB0002299,HMDB0000202,HMDB0002166,HMDB0000023,HMDB0002217
#> Porphyrin and chlorophyll metabolism                                                                                                                                                                                                                                                                                                                                                                                                            HMDB0000148,HMDB0000123,HMDB0000167,HMDB0001149,HMDB0001008,HMDB0000245,HMDB0013233,HMDB0001261,HMDB0002158,HMDB0004157,HMDB0004161,HMDB0000692
#> Sphingolipid metabolism                                                                                                                                                                                                                                                                                                                                                                                                                                                             HMDB0000187,HMDB0000252,HMDB0000224,HMDB0001383,HMDB0004866,HMDB0000648,HMDB0001480,HMDB0000277,HMDB0006752
#> Estrogen signaling pathway                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          HMDB0000112
#> One carbon pool by folate                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               HMDB0000972,HMDB0001562

We note that applying the multiple-matching penalty using parameter fractional.count.power will effectively making fractional counts out of the multiple-matched features. Thus the mapped feature tables, you will see fractional counts, rather than integer counts.

ftable(r)[which(ptable(r)[,1]<0.025 & ptable(r)[,2]>=2)]
#> $`Glycosphingolipid metabolism`
#>      m.z      retention.time p.value    statistic HMDB_ID       m.z     
#> [1,] 380.2564 517.4015       0.02576156 2.263223  "HMDB0000277" 380.256 
#> [2,] 282.2793 522.1412       0.03861876 2.095591  "HMDB0001551" 282.2791
#> [3,] 371.3268 546.4621       0.02881342 -2.217735 "HMDB0006752" 371.3268
#> [4,] 179.0563 104.8357       0.02843861 -2.191182 "HMDB0000122" 179.0561
#> [5,] 179.0563 104.8357       0.02843861 -2.191182 "HMDB0003449" 179.0561
#> [6,] 380.2575 194.7167       0.02327888 -2.268827 "HMDB0001383" 380.2571
#>      ion.type  counts   
#> [1,] "M+H"     0.2672612
#> [2,] "M+ACN+H" 0.5      
#> [3,] "M+ACN+H" 0.7071068
#> [4,] "M-H"     0.1825742
#> [5,] "M-H"     0.1825742
#> [6,] "M-H"     1        
#> 
#> $`C21-steroid hormone biosynthesis and metabolism`
#>       m.z      retention.time p.value    statistic HMDB_ID       m.z     
#>  [1,] 380.2564 517.4015       0.02576156 2.263223  "HMDB0000253" 380.256 
#>  [2,] 380.2564 517.4015       0.02576156 2.263223  "HMDB0003069" 380.256 
#>  [3,] 482.3603 568.9371       0.04738957 -2.007298 "HMDB0006280" 482.3605
#>  [4,] 482.3603 568.9371       0.04738957 -2.007298 "HMDB0006281" 482.3605
#>  [5,] 482.3603 568.9371       0.04738957 -2.007298 "HMDB0006763" 482.3605
#>  [6,] 465.2501 180.1967       0.01296878 2.484626  "HMDB0002829" 465.2494
#>  [7,] 465.2501 180.1967       0.01296878 2.484626  "HMDB0004484" 465.2494
#>  [8,] 465.2501 180.1967       0.01296878 2.484626  "HMDB0006203" 465.2494
#>  [9,] 465.3047 178.2345       0.03315628 -2.130186 "HMDB0000653" 465.3044
#> [10,] 349.1476 235.4682       0.02916411 2.181261  "HMDB0001032" 349.1474
#> [11,] 349.1476 235.4682       0.02916411 2.181261  "HMDB0002833" 349.1474
#>       ion.type   counts   
#>  [1,] "M+ACN+Na" 0.2672612
#>  [2,] "M+ACN+Na" 0.2672612
#>  [3,] "M+ACN+Na" 0.2672612
#>  [4,] "M+ACN+Na" 0.2672612
#>  [5,] "M+ACN+Na" 0.2672612
#>  [6,] "M-H"      0.5      
#>  [7,] "M-H"      0.5      
#>  [8,] "M-H"      0.5      
#>  [9,] "M-H"      1        
#> [10,] "M-H2O-H"  0.5      
#> [11,] "M-H2O-H"  0.5      
#> 
#> $`Porphyrin Metabolism`
#>      m.z      retention.time p.value    statistic HMDB_ID       m.z     
#> [1,] 91.00046 74.11095       0.0369492  -2.114328 "HMDB0003125" 91.00018
#> [2,] 583.2549 175.0813       0.01153899 2.525938  "HMDB0000054" 583.2562
#> [3,] 641.2961 221.7938       0.04707521 1.985623  "HMDB0001261" 641.2975
#> [4,] 641.2961 221.7938       0.04707521 1.985623  "HMDB0002158" 641.2975
#>      ion.type  counts   
#> [1,] "2M+Na"   1        
#> [2,] "M-H"     0.7071068
#> [3,] "M-H2O-H" 0.7071068
#> [4,] "M-H2O-H" 0.7071068
#> 
#> $`Purine Metabolism`
#>      m.z      retention.time p.value      statistic HMDB_ID       m.z     
#> [1,] 137.0457 102.6127       0.01490208   2.477191  "HMDB0000157" 137.0458
#> [2,] 148.0605 145.3059       6.477547e-05 4.168804  "HMDB0000148" 148.0604
#> [3,] 169.0357 129.7487       2.198944e-05 4.451891  "HMDB0000289" 169.0356
#> [4,] 176.0658 95.71658       0.007465356  2.730395  "HMDB0001005" 176.0666
#> [5,] 210.0622 124.1626       0.01731002   2.419944  "HMDB0000289" 210.0622
#> [6,] 91.00046 74.11095       0.0369492    -2.114328 "HMDB0003125" 91.00018
#> [7,] 472.1565 235.4289       0.03463024   2.112656  "HMDB0000972" 472.1586
#> [8,] 168.0246 22.15699       0.02175471   2.294624  "HMDB0001517" 168.0241
#>      ion.type  counts   
#> [1,] "M+H"     0.4472136
#> [2,] "M+H"     0.2182179
#> [3,] "M+H"     0.7071068
#> [4,] "M+ACN+H" 0.5      
#> [5,] "M+ACN+H" 1        
#> [6,] "2M+Na"   1        
#> [7,] "M-H"     0.4472136
#> [8,] "M-2H"    0.3535534
#> 
#> $`Sphingolipid Metabolism`
#>      m.z      retention.time p.value    statistic HMDB_ID       m.z     
#> [1,] 380.2564 517.4015       0.02576156 2.263223  "HMDB0000277" 380.256 
#> [2,] 282.2793 522.1412       0.03861876 2.095591  "HMDB0001551" 282.2791
#> [3,] 371.3268 546.4621       0.02881342 -2.217735 "HMDB0006752" 371.3268
#> [4,] 179.0563 104.8357       0.02843861 -2.191182 "HMDB0000122" 179.0561
#> [5,] 179.0563 104.8357       0.02843861 -2.191182 "HMDB0000143" 179.0561
#> [6,] 380.2575 194.7167       0.02327888 -2.268827 "HMDB0001383" 380.2571
#>      ion.type  counts   
#> [1,] "M+H"     0.2672612
#> [2,] "M+ACN+H" 0.5      
#> [3,] "M+ACN+H" 0.7071068
#> [4,] "M-H"     0.1825742
#> [5,] "M-H"     0.1825742
#> [6,] "M-H"     1        
#> 
#> $`Glycine, serine and threonine metabolism`
#>       m.z      retention.time p.value      statistic HMDB_ID       m.z     
#>  [1,] 104.0711 161.4844       0.0006262675 3.530572  "HMDB0000092" 104.0706
#>  [2,] 118.0865 123.9865       0.00925984   2.653289  "HMDB0000043" 118.0863
#>  [3,] 132.0769 120.2762       0.002813653  3.062472  "HMDB0000064" 132.0768
#>  [4,] 154.0588 104.7939       0.0003642482 3.68944   "HMDB0000064" 154.0587
#>  [5,] 148.0605 145.3059       6.477547e-05 4.168804  "HMDB0000139" 148.0604
#>  [6,] 159.0765 108.9502       0.02020321   -2.359876 "HMDB0006454" 159.0764
#>  [7,] 159.0765 108.9502       0.02020321   -2.359876 "HMDB0012249" 159.0764
#>  [8,] 156.1133 53.23243       0.03377114   2.152113  "HMDB0002134" 156.1131
#>  [9,] 116.0717 171.0386       0.01687998   2.389311  "HMDB0000043" 116.0717
#>       ion.type   counts   
#>  [1,] "M+H"      0.2085144
#>  [2,] "M+H"      0.1856953
#>  [3,] "M+H"      0.3779645
#>  [4,] "M+Na"     0.5773503
#>  [5,] "M+ACN+H"  0.2182179
#>  [6,] "M+ACN+H"  0.3779645
#>  [7,] "M+ACN+H"  0.3779645
#>  [8,] "M+2ACN+H" 0.3015113
#>  [9,] "M-H"      0.3779645
#> 
#> $`Protein digestion and absorption`
#>       m.z      retention.time p.value      statistic HMDB_ID       m.z     
#>  [1,] 118.0865 123.9865       0.00925984   2.653289  "HMDB0000883" 118.0863
#>  [2,] 132.102  112.3156       0.00101215   3.385782  "HMDB0000172" 132.1019
#>  [3,] 132.102  112.3156       0.00101215   3.385782  "HMDB0000687" 132.1019
#>  [4,] 148.0605 145.3059       6.477547e-05 4.168804  "HMDB0000148" 148.0604
#>  [5,] 182.0812 126.5291       0.0026755    3.078928  "HMDB0000158" 182.0812
#>  [6,] 241.031  134.0609       0.003110045  3.029553  "HMDB0000192" 241.0311
#>  [7,] 144.102  186.3768       0.04303946   -2.049156 "HMDB0000718" 144.1019
#>  [8,] 144.102  186.3768       0.04303946   -2.049156 "HMDB0002176" 144.1019
#>  [9,] 173.1285 108.9319       0.009278025  2.65258   "HMDB0000172" 173.1285
#> [10,] 173.1285 108.9319       0.009278025  2.65258   "HMDB0000687" 173.1285
#> [11,] 246.1698 84.69621       0.001125517  3.3532    "HMDB0000718" 246.17  
#> [12,] 246.1698 84.69621       0.001125517  3.3532    "HMDB0002176" 246.17  
#> [13,] 116.0717 171.0386       0.01687998   2.389311  "HMDB0000883" 116.0717
#>       ion.type   counts   
#>  [1,] "M+H"      0.1856953
#>  [2,] "M+H"      0.1666667
#>  [3,] "M+H"      0.1666667
#>  [4,] "M+H"      0.2182179
#>  [5,] "M+H"      0.164399 
#>  [6,] "M+H"      1        
#>  [7,] "M+ACN+H"  0.1767767
#>  [8,] "M+ACN+H"  0.1767767
#>  [9,] "M+ACN+H"  0.2294157
#> [10,] "M+ACN+H"  0.2294157
#> [11,] "2M+ACN+H" 0.1924501
#> [12,] "2M+ACN+H" 0.1924501
#> [13,] "M-H"      0.3779645
#> 
#> $`Biosynthesis of alkaloids derived from histidine and purine`
#>      m.z      retention.time p.value     statistic HMDB_ID       m.z     
#> [1,] 132.102  112.3156       0.00101215  3.385782  "HMDB0000687" 132.1019
#> [2,] 144.102  186.3768       0.04303946  -2.049156 "HMDB0000718" 144.1019
#> [3,] 173.1285 108.9319       0.009278025 2.65258   "HMDB0000687" 173.1285
#> [4,] 246.1698 84.69621       0.001125517 3.3532    "HMDB0000718" 246.17  
#> [5,] 117.0195 42.31922       0.01629752  -2.402184 "HMDB0000254" 117.0193
#> [6,] 179.0563 104.8357       0.02843861  -2.191182 "HMDB0003345" 179.0561
#> [7,] 168.0246 22.15699       0.02175471  2.294624  "HMDB0001517" 168.0241
#> [8,] 175.0622 281.0827       0.04714144  1.985027  "HMDB0001847" 175.062 
#>      ion.type   counts   
#> [1,] "M+H"      0.1666667
#> [2,] "M+ACN+H"  0.1767767
#> [3,] "M+ACN+H"  0.2294157
#> [4,] "2M+ACN+H" 0.1924501
#> [5,] "M-H"      0.2886751
#> [6,] "M-H"      0.1825742
#> [7,] "M-2H"     0.3535534
#> [8,] "M-H2O-H"  0.5773503
#> 
#> $`Valine, leucine and isoleucine degradation`
#>       m.z      retention.time p.value      statistic HMDB_ID       m.z     
#>  [1,] 104.0711 161.4844       0.0006262675 3.530572  "HMDB0002166" 104.0706
#>  [2,] 104.0711 161.4844       0.0006262675 3.530572  "HMDB0002299" 104.0706
#>  [3,] 118.0865 123.9865       0.00925984   2.653289  "HMDB0000883" 118.0863
#>  [4,] 132.102  112.3156       0.00101215   3.385782  "HMDB0000172" 132.1019
#>  [5,] 132.102  112.3156       0.00101215   3.385782  "HMDB0000687" 132.1019
#>  [6,] 173.1285 108.9319       0.009278025  2.65258   "HMDB0000172" 173.1285
#>  [7,] 173.1285 108.9319       0.009278025  2.65258   "HMDB0000687" 173.1285
#>  [8,] 116.0717 171.0386       0.01687998   2.389311  "HMDB0000883" 116.0717
#>  [9,] 117.0195 42.31922       0.01629752   -2.402184 "HMDB0000202" 117.0193
#>       ion.type  counts   
#>  [1,] "M+H"     0.2085144
#>  [2,] "M+H"     0.2085144
#>  [3,] "M+H"     0.1856953
#>  [4,] "M+H"     0.1666667
#>  [5,] "M+H"     0.1666667
#>  [6,] "M+ACN+H" 0.2294157
#>  [7,] "M+ACN+H" 0.2294157
#>  [8,] "M-H"     0.3779645
#>  [9,] "M-H"     0.2886751