PathwayExplorer: web service for visualizing high-throughput expression data on biological pathways

Abstract

While generation of high-throughput expression data is becoming routine, the fast, easy, and systematic presentation and analysis of these data in a biological context is still an obstacle. To address this need, we have developed PathwayExplorer, which maps expression profiles of genes or proteins simultaneously onto major, currently available regulatory, metabolic and cellular pathways from KEGG, BioCarta and GenMAPP. PathwayExplorer is a platform-independent web server application with an optional standalone Java application using a SOAP (simple object access protocol) interface. Mapped pathways are ranked for the easy selection of the pathway of interest, displaying all available genes of this pathway with their expression profiles in a selectable and intuitive color code. Pathway maps produced can be downloaded as PNG, JPG or as high-resolution vector graphics SVG. The web service is freely available at https://pathwayexplorer.genome.tugraz.at; the standalone client can be downloaded at http://genome.tugraz.at.

Figure 1

PathwayExplorer example: a screenshot of a pathway mapped with expression data. (i) The toolbar frame (the row including the organism field) offers various setup and visualization options. (ii) Hierarchical tree frame (on the left) enables browsing through all available pathway sections. (iii) The main frame (in the center) displays the citrate cycle pathway extracted from KEGG, which mapped with a yeast sporulation data set with seven different time points (0, 0.5, 2, 5, 7, 8 and 11.5 h). The color-coded boxes represent mapped genes. If more than just one gene ID (e.g. RefSeq) matches to a box, each box is split up into several horizontal elements. According to the number of experiments/time points (in this case seven time points), the boxes are split again into vertical columns which display the expression level of each time point. To visualize a mapped expression profile in a different way, one has to choose the corresponding horizontal row of a box (see Figure 2).

Figure 2

By selecting one row (if there are more than one) of a mapped gene box (Figure 1), the corresponding gene and expression profile information will be displayed. To obtain additional information links to GenBank, Entrez and OMIM are provided. Only one mapped expression profile from the uploaded data set can be displayed at once.

Figure 3

(a) Shows the overall statistic of the filtered unique identifiers of the expression data set mapped on all pathways. (b) The ranking list of all mapped pathways is also displayed and can be sorted by different criteria, allowing easy navigation through all pathways. By selecting the pathway of interest, the data set will be automatically mapped on the pathway and the expression values will be displayed in a selectable and intuitive color code (see Figure 1). The last two columns display the P-value and the FDR (19) corrected Q-value.