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Table 5 Hypergeometric probability of KEGG defined metabolic pathways in bottom cluster in Figure 11

From: Exploring metabolic pathway disruption in the subchronic phencyclidine model of schizophrenia with the Generalized Singular Value Decomposition

KEGG Path-way Identity

KEGG Pathway

Number of metabolites in cluster(A)

Total number of pathway metabolites detected (B)

Hypergeometric Probability (P(X) ≥ k)

ko00010

Glycolysis/Gluconeogenesis

1

1

0.184

ko00051

Fructose and Mannose metabolism

1

1

0.184

ko00052

Galactose metabolism

1

1

0.184

ko00071

Fatty acid metabolism

1

1

0.184

ko00230

Purine metabolism

4

13

0.191

ko00260

Glycine, Serine and Threonine metabolism

1

7

0.770

ko00270

Cysteine and Methionine metabolism

1

7

0.770

ko00340

Histidine metabolism

1

5

0.646

ko00410

beta-Alanine metabolism

1

5

0.646

ko00430

Taurine and Hypotaurine metabolism

1

3

0.460

ko00440

Phosphonate and Phosphinate metabolism

1

2

0.335

ko00480

Glutathione metabolism

1

5

0.646

ko00561

Glycerolipid metabolism

1

2

0.335

ko00562

Inositol Phosphate metabolism

1

2

0.335

ko00564

Glycerphopholipid metabolism

2

11

0.642

ko00620

Pyruvate metabolism

1

2

0.335

map00650

Butanoate metabolism

1

4

0.562

ko00730

Thiamine metabolism

1

1

0.184

ko00770

Pantothenate and CoA biosynthesis

1

5

0.646

map00920

Sulphur metabolism

1

3

0.460

  1. Table 5 shows the hypergeometric probability of randomly seeing at least the observed number of metabolites of a given KEGG pathway in the bottom cluster of Figure 11, identified though the GSVD algorithm as being present in control animals but not in PCP-treated animals. There was no evidence for a particular over-abundance of metabolites from any given KEGG pathway in this cluster. Cluster size is 18 metabolites from a total population of 98.