Metabolomic Data Analysis with metaX
Introduction

Metabolomics is a growing and powerful technology capable of detecting hundreds to thousands of metabolites in tissues and biofluids. metabolomics alterations represent changes in the phenotype and molecular physiology.

Methods and Data
Summary of Data Set

Table 1.  Sample group information.

class n
C 66
QC 38
S 68

Table 2.  Experiment batch information.

batch n
1 91
5 17
6 20
7 44

Table 3.  Sample information.

sample batch class order
batch01_QC01 1 QC 1
batch01_QC02 1 QC 2
batch01_QC03 1 QC 3
batch01_C05 1 C 4
batch01_S07 1 S 5
batch01_C10 1 C 6
batch01_QC04 1 QC 7
batch01_S01 1 S 8
batch01_C03 1 C 9
batch01_S05 1 S 10
batch01_C07 1 C 11
batch01_S06 1 S 12
batch01_QC05 1 QC 13
batch01_C08 1 C 14
batch01_C06 1 C 15
batch01_S02 1 S 16
batch01_S09 1 S 17
batch01_QC06 1 QC 18
batch01_S04 1 S 19
batch01_C04 1 C 20
batch01_S10 1 S 21
batch01_C09 1 C 22
batch01_QC07 1 QC 23
batch02_C05 1 C 24
batch02_S03 1 S 25
batch02_S07 1 S 26
batch02_C01 1 C 27
batch02_C10 1 C 28
batch02_QC08 1 QC 29
batch02_S01 1 S 30
batch02_C03 1 C 31
batch02_S05 1 S 32
batch02_C07 1 C 33
batch02_S06 1 S 34
batch02_QC09 1 QC 35
batch02_C08 1 C 36
batch02_C06 1 C 37
batch02_S02 1 S 38
batch02_S09 1 S 39
batch02_C02 1 C 40
batch02_QC10 1 QC 41
batch02_S04 1 S 42
batch02_S08 1 S 43
batch02_C04 1 C 44
batch02_S10 1 S 45
batch02_C09 1 C 46
batch02_QC11 1 QC 47
batch03_C05 1 C 48
batch03_S03 1 S 49
batch03_S07 1 S 50
batch03_C01 1 C 51
batch03_C10 1 C 52
batch03_QC12 1 QC 53
batch03_S01 1 S 54
batch03_C03 1 C 55
batch03_S05 1 S 56
batch03_C07 1 C 57
batch03_S06 1 S 58
batch03_QC13 1 QC 59
batch03_C08 1 C 60
batch03_C06 1 C 61
batch03_S02 1 S 62
batch03_S09 1 S 63
batch03_C02 1 C 64
batch03_QC14 1 QC 65
batch03_S04 1 S 66
batch03_S08 1 S 67
batch03_C04 1 C 68
batch03_S10 1 S 69
batch03_C09 1 C 70
batch03_QC15 1 QC 71
batch04_C05 1 C 72
batch04_S03 1 S 73
batch04_S07 1 S 74
batch04_C01 1 C 75
batch04_QC16 1 QC 76
batch04_S01 1 S 77
batch04_S05 1 S 78
batch04_C07 1 C 79
batch04_S06 1 S 80
batch04_QC17 1 QC 81
batch04_C08 1 C 82
batch04_C06 1 C 83
batch04_S02 1 S 84
batch04_S09 1 S 85
batch04_C02 1 C 86
batch04_QC18 1 QC 87
batch04_S08 1 S 88
batch04_C04 1 C 89
batch04_S10 1 S 90
batch04_QC19 1 QC 91
batch05_QC20 5 QC 92
batch05_S03 5 S 93
batch05_S07 5 S 94
batch05_C01 5 C 95
batch05_C10 5 C 96
batch05_QC21 5 QC 97
batch05_S01 5 S 98
batch05_C03 5 C 99
batch05_C07 5 C 100
batch05_QC22 5 QC 101
batch05_C06 5 C 102
batch05_C02 5 C 103
batch05_QC23 5 QC 104
batch05_S04 5 S 105
batch05_S08 5 S 106
batch05_C04 5 C 107
batch05_QC24 5 QC 108
batch06_QC25 6 QC 109
batch06_S03 6 S 110
batch06_C10 6 C 111
batch06_QC26 6 QC 112
batch06_S01 6 S 113
batch06_C03 6 C 114
batch06_S05 6 S 115
batch06_C07 6 C 116
batch06_S06 6 S 117
batch06_QC27 6 QC 118
batch06_C08 6 C 119
batch06_C06 6 C 120
batch06_S02 6 S 121
batch06_C02 6 C 122
batch06_QC28 6 QC 123
batch06_S04 6 S 124
batch06_S08 6 S 125
batch06_C04 6 C 126
batch06_C09 6 C 127
batch06_QC29 6 QC 128
batch07_QC30 7 QC 129
batch07_C05 7 C 130
batch07_S03 7 S 131
batch07_S07 7 S 132
batch07_C01 7 C 133
batch07_C10 7 C 134
batch07_QC31 7 QC 135
batch07_C03 7 C 136
batch07_S05 7 S 137
batch07_C07 7 C 138
batch07_S06 7 S 139
batch07_QC32 7 QC 140
batch07_C08 7 C 141
batch07_S02 7 S 142
batch07_S09 7 S 143
batch07_C02 7 C 144
batch07_QC33 7 QC 145
batch07_S04 7 S 146
batch07_S08 7 S 147
batch07_S10 7 S 148
batch07_C09 7 C 149
batch07_QC34 7 QC 150
batch08_C05 7 C 151
batch08_S03 7 S 152
batch08_S07 7 S 153
batch08_C01 7 C 154
batch08_C10 7 C 155
batch08_QC36 7 QC 156
batch08_S01 7 S 157
batch08_C03 7 C 158
batch08_S05 7 S 159
batch08_C07 7 C 160
batch08_S06 7 S 161
batch08_QC37 7 QC 162
batch08_C08 7 C 163
batch08_S02 7 S 164
batch08_S09 7 S 165
batch08_QC38 7 QC 166
batch08_S04 7 S 167
batch08_S08 7 S 168
batch08_C04 7 C 169
batch08_S10 7 S 170
batch08_C09 7 C 171
batch08_QC39 7 QC 172
Results
Data quality analysis

This part contains the basic data quality.

Remove peaks in QC samples with missing value greater than 50 percent:35.

Remove peaks in non-QC samples with missing value greater than 80 percent:0.

Figure 1.  Get High-res Image Peak number distribution.

Figure 2.  Get High-res Image Peak CV distribution.

Table 4.  CV stat.

class n n30 n20 n30ratio n20ratio
C 2453 765 196 0.31 0.08
QC 2453 1624 840 0.66 0.34
S 2453 1043 236 0.43 0.096

Figure 3.  Get High-res Image Missing value distribution.

Figure 4.  Get High-res Image Peak intensity distribution.

Figure 5.  Get High-res Image Correlation heatmap.

Figure 6.  Get High-res Image TIC distribution.

The missing value were imputed by knn.

The data was normalized by QC-RLSC.

Table 5.  CV summary after QC-RLSC for each batch.

batch CV lessThan30 total ratio
1 rawCV 2256 2453 0.92
1 normCV 2354 2453 0.96
5 rawCV 2295 2453 0.94
5 normCV 2385 2453 0.97
6 rawCV 2300 2453 0.94
6 normCV 2400 2453 0.98
7 rawCV 2312 2453 0.94
7 normCV 2406 2453 0.98

Table 6.  CV summary after QC-RLSC for all samples.

CV lessThan30 total ratio
rawCV 1925 2453 0.78
normCV 2396 2453 0.98

Figure 7.  Get High-res Image QC-RLSC figure.

Data quality check after normalization and pre-processing.

Figure 8.  Get High-res Image Correlation heatmap.

Figure 9.  Get High-res Image Peak intensity distribution.

Figure 10.  Get High-res Image TIC distribution.

Figure 11.  Get High-res Image Heatmap.

Figure 12.  Get High-res Image PCA.

Metabolite quantification and identification.

This part contains the quantification and identification.

Table 7.  Get Full Table Metabolite quantification result.

ID ratio t.test p.value wilcox.test p.value t.test p.value BHcorrect wilcox.test p.value BHcorrect roc lowROC upROC VIP sample rawCV cv
100.99362 2.2 8.2e-26 3e-20 6.4e-25 2.4e-19 0.96 0.93 0.99 1.6 S:C 0.17 0.082
100.99992 0.96 0.22 0.35 0.27 0.41 0.55 0.45 0.65 0.34 S:C 0.21 0.12
102.09132 0.99 0.81 0.89 0.84 0.91 0.49 0.39 0.58 0.075 S:C 0.57 0.048
103.03826 1 0.76 1 0.8 1 0.5 0.41 0.61 0.07 S:C 0.76 0.11
103.03855 0.99 0.98 0.96 0.98 0.97 0.5 0.4 0.59 0.0069 S:C 0.78 0.048
103.03895 1 0.47 0.56 0.54 0.62 0.53 0.42 0.62 0.13 S:C 0.69 0.055
104.07059 0.79 1.8e-06 3.3e-06 4e-06 7.4e-06 0.73 0.64 0.81 0.87 S:C 0.12 0.043
104.10656 0.62 1.2e-16 8.9e-14 5.4e-16 3.5e-13 0.87 0.81 0.92 1.4 S:C 0.12 0.088
104.10698 0.62 4e-16 2.8e-14 1.8e-15 1.1e-13 0.88 0.83 0.93 1.4 S:C 0.17 0.1
106.95057 0.81 1.5e-09 3.6e-09 4.1e-09 9.9e-09 0.8 0.71 0.86 1 S:C 0.16 0.072
108.06551 0.84 0.0023 0.0055 0.004 0.0093 0.64 0.54 0.73 0.55 S:C 0.24 0.14
110.07126 2 8.5e-22 2e-18 5.2e-21 1.2e-17 0.94 0.89 0.98 1.5 S:C 0.26 0.058
112.01591 1 0.42 0.45 0.48 0.52 0.46 0.36 0.57 0.2 S:C 0.41 0.07
112.03689 0.76 4.2e-13 1.7e-11 1.5e-12 5.4e-11 0.84 0.77 0.9 1.2 S:C 0.12 0.065
112.0523 0.45 1.3e-12 8.5e-17 4.4e-12 4.4e-16 0.92 0.85 0.97 1.2 S:C 0.43 0.057
112.08692 2.4 9.4e-43 2e-23 2.8e-41 4.2e-22 1 1 1 1.9 S:C 0.18 0.038
113.00835 0.96 0.38 0.59 0.45 0.65 0.53 0.43 0.62 0.16 S:C 0.24 0.053
113.02091 0.93 0.031 0.045 0.046 0.065 0.6 0.49 0.69 0.42 S:C 0.24 0.048
113.05565 0.49 5.1e-19 5.6e-16 2.7e-18 2.7e-15 0.91 0.84 0.96 1.5 S:C 0.33 0.074
113.99518 0.84 0.0022 0.00088 0.0039 0.0016 0.67 0.57 0.76 0.55 S:C 0.22 0.11