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7. KnetMiner Support for new data (concept) types in KnetMaps
When integrating novel data resulting in the presence of new conceptClasses
and relationTypes
in the knowledge network oxl
, the following customizations need to be undertaken to render the new concepts in the KnetMiner user interface, i.e., in KnetMaps (Network View), Evidence View legend and the dynamic, interactive legends for Gene View and KnetMaps:
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For KnetMaps, all visual attributes (color, shape, size) for concept and relations are defined in the
cyjsJSON
Exporter plugin module in theondex-knet-builder
platform for data integration. This module generates JSON, after a KnetMiner search, when a gene is selected to view its sub-network in KnetMaps (Network View). So, for any new concept classes, e.g, DGES, PO and COEXPS, users must add them toConceptType.java
within thecyjsJSON
module and add any new concept shape and color options there similarly as well. Permitted shapes for later visualization in KnetMiner can be seen inConceptShape.java
. Note: These .java classes areEnums
(containing constants) which are used as config files, without the overhead of parsing separate XML config files and with added type-safety. Once the concept and relation types and their visual attributes are added here, they are exported as JSON whenever KnetMaps is invoked within KnetMiner.Note: If these parameters are not defined, the exporter plugin will use default values to customize the new concepts (
shape: roundrectangle, color: greenYellow
, like for Phenotype concepts) and relations (color: black
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Once the above is added and KnetMiner server .jar is deployed, users can visualize these new concept and relation types within KnetMiner. The next step is to add images of these new concept types in the image repository in KnetMiner client. This can be easily done via a KnetMiner search and then opening a sub-network for a gene in KnetMaps from where users can extract the concept's icon (e.g., as a
png
image) and add it to the aboveimage
folder. The Gene View and KnetMaps legend are both generated dynamically based on what concept types are present in the current search or the current sub-network being visualized but look at thisimage
repository for images to add to the legend. Without adding these images, the legend will show concept type (and count) but not the image.