Hello I’m Kozo Nishida I introduce KEGG data import plugin. I will demostrate after talk.
This is the outline of my talk. I talk about KEGG data import plugin named KGMLReader , the new VizMap on the imported pathway. , the annotation import using TogoWS webservice. , and future plans of this project.
First I talk about KEGG data import
I introduce KEGG. KEGG is one of the most comprehensive database of human-curated pathways. KEGG has grown, many new features have been incorporated. This is one of the new features, global metabolism map. And KEGG include not only pathway database but these databases. These data are widely used in bioinformatics analysis. So we have developed a plug-in to import these data into Cytoscape.
The plug-in name is KGMLReader. This plug-in reads KGML and build a network almost same with KEGG like this. KGML is a xml format of KEGG graph objects and contains diagram component coordinate. This network coordinate is important, because this biologist familiar layout helps users understand the biological process than non-layouted one. As far as I know, Biopax or SBML doesn't hold this layout information.
KGMLReader supports all metabolic pathways which include KEGG new pathway called global metabolism map. This global map is useful to compare the entire metabolism in different organism Or conditions such as dynamical changes of gene expressions in a time-series microarray experiment. This is an image from KEGG website.
And this is the global map imported to Cytoscape by KGMLReader. Each gray colored node is pathway. In this case, this node is TCA cycle. For example I'll show 3 organism global metabolism map in Cytoscape.
This is for Ecoli.
This is for Yeast.
This is for human. In this way, users can compare the annotated metabolic reaction between organism in KEGG using Cytoscape.
Next I show some VizMap examples on the imported KEGG pathways.
This is the example of the time-series expression transition on global metabolism map. Colored nodes are pathway nodes which are significantly over or under-expressed in mutant than WT. I performed two sample t-tests on vectors of expression assigned to each pathway. Red is over-expressed in MT. Green is under-expressed in MT. This VizMap for time-series 1.
this is for time-series 2
this is for time-series 3
this is for time-series 4
this is for time-series 5
this is for time-series 6 This is useful to compare dynamical changes of gene expressions in a time-series microarray experiment.
In addition, Users can use custom node graphics in coming Cytoscape 2.8. These charts are generated by Google chart tools. This is an example of custom node graphics on the imported pathway. These charts are time-series expression profiles of enzyme genes. Red and blue lines are gene expression profiles. Red is mutant. Blue is WT. And the background color orange and blue means significantly over or under-expressed in mutant than WT in KEGG module. KEGG module is subset of pathway, and set of several reactions.
Next I talk about annotation import using TogoWS.
KGML has the component entry_id and short name, however does not have id-links to other database, and other useful KEGG metadata. So we added TogoWS web-service client to get these data from entry_id.
TogoWS is one-stop service for major biological databases which include KEGG. Users can get each KEGG entry field by requesting simple REST URL.
This is an example of such field extraction And This is imported network attribute for a pathway bsu00010.
At the end I talk about the future plan about this project.
In global map colored nodes are pathway maplink nodes. So we will add function that jump to or generate network with clicking or selecting maplink nodes, using Nested Network Format.
VizMap manual change for many KEGG attributes is troublesome. So we will add a KEGG specialized search and selection input box.
And we will add floating information windows. We will use this for boxplot for expression or centrality diversity of each pathway and other network statistics.
And We will add side-by-side network comparison UI. In this case I’m comparing different orgnism. This can be applied to other Visual Style For example left side is expression and right side is centrality. Left side is expression time-series1 and right side is expression time-series2.
This is other future plan list. For more details, please ask us in poster sessions.
I would like to thank these people. And next I demonstrate KGMLReader.
Importing KEGG pathway and mapping custom node graphics on Cytoscape Kozo Nishida Keiichiro Ono Cytoscape retreat 2010 University of Michigan Jul 18, 2010
Lysine biosynthesis red line = expression profile(MT) blue line= expression profile(WT) orange background = over-expressed in MT than WT(Pval < 0.05) for KEGG module blue background = under-expressed....