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Comparative Study
. 2002 Jul;12(7):1121-6.
doi: 10.1101/gr.226602.

Pathway Processor: a tool for integrating whole-genome expression results into metabolic networks

Paul Grosu  1 , Jeffrey P Townsend, Daniel L Hartl, Duccio Cavalieri
Affiliations
Comparative Study

Pathway Processor: a tool for integrating whole-genome expression results into metabolic networks

Paul Grosu et al. Genome Res. 2002 Jul.

Abstract

We have developed a new tool to visualize expression data on metabolic pathways and to evaluate which metabolic pathways are most affected by transcriptional changes in whole-genome expression experiments. Using the Fisher Exact Test, the method scores biochemical pathways according to the probability that as many or more genes in a pathway would be significantly altered in a given experiment by chance alone. This method has been validated on diauxic shift experiments and reproduces well known effects of carbon source on yeast metabolism. The analysis is implemented with Pathway Analyzer, one of the tools of Pathway Processor, a new statistical package for the analysis of whole-genome expression data. Results from multiple experiments can be compared, reducing the analysis from the full set of individual genes to a limited number of pathways of interest. The pathways are visualized with OpenDX, an open-source visualization software package, and the relationship between genes in the pathways can be examined in detail using Expression Mapper, the second program of the package. This program features a graphical output displaying differences in expression on metabolic charts of the biochemical pathways to which the open reading frames are assigned.

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Figures

Figure 1
Figure 1
Pathway Analyzer results showing the 15 most activated pathways (A) and the 15 most repressed pathways (B) for the seven timepoints of the diauxic shift experiments. The columns from T1 to T7 report the P-values of the Signed Fisher Exact Test, obtained from the comparison of relative expression at T0 to that at the different timepoints of the diauxic shift experiments, with T1 = 9 h, T2 = 11 h, T3 = 13 h, T4 = 15 h, T5 = 17 h, T6 = 19 h, and T7 = 21 h. The data have been sorted according to their ranking in the last experiment, T7 versus T0. The pathways are visualized using OpenDX. The color of the cube indicates the sign of the variation, with red being up-regulated, green down-regulated, and yellow no change. The opacity represents the statistical significance of the variation: the greater the opacity, the smaller the P-value. The color of the cube depends on the P-value in the following way: from 1 to 0.15 the color remains yellow, from 0.15 to 0 with overexpression (+) it goes from yellow to red, and from 0.15 to 0 with underexpression (−) it goes from yellow to green.
Figure 2
Figure 2
Part of the Expression Mapper output for valine, leucine, and isoleucine metabolism, adapted from KEGG map 290. The text is colored red if the relative change in gene expression is ≥1, and green if it is <1. The intensity of the color is proportional to the magnitude of the differential expression. The presence of a gray box indicates that the corresponding step in the biochemical pathway requires multiple gene products.
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