title: PANDA: pathway and annotation explorer for visualizing and interpreting gene-centric data.
abstract: Objective. Bringing together genomics, transcriptomics, proteomics, and other -omics technologies is an important step towards developing highly personalized medicine. However, instrumentation has advances far beyond expectations and now we are able to generate data faster than it can be interpreted. Materials and Methods. We have developed PANDA (Pathway AND Annotation) Explorer, a visualization tool that integrates gene-level annotation in the context of biological pathways to help interpret complex data from disparate sources. PANDA is a web-based application that displays data in the context of well-studied pathways like KEGG, BioCarta, and PharmGKB. PANDA represents data/annotations as icons in the graph while maintaining the other data elements (i.e., other columns for the table of annotations). Custom pathways from underrepresented diseases can be imported when existing data sources are inadequate. PANDA also allows sharing annotations among collaborators. Results. In our first use case, we show how easy it is to view supplemental data from a manuscript in the context of a user's own data. Another use-case is provided describing how PANDA was leveraged to design a treatment strategy from the somatic variants found in the tumor of a patient with metastatic sarcomatoid renal cell carcinoma. Conclusion. PANDA facilitates the interpretation of gene-centric annotations by visually integrating this information with context of biological pathways. The application can be downloaded or used directly from our website: http://bioinformaticstools.mayo.edu/research/panda-viewer/.
authors.affiliation: Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
authors.forename: Steven N
authors.initials: SN
authors.lastname: Hart
authors.affiliation: Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
authors.forename: Raymond M
authors.initials: RM
authors.lastname: Moore
authors.affiliation: Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
authors.forename: Michael T
authors.initials: MT
authors.lastname: Zimmermann
authors.affiliation: Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
authors.forename: Gavin R
authors.initials: GR
authors.lastname: Oliver
authors.affiliation: Division of Hematology/Oncology Mayo Clinic, Mayo Clinic Cancer Center, Scottsdale, AZ, USA.
authors.forename: Jan B
authors.initials: JB
authors.lastname: Egan
authors.affiliation: Division of Hematology/Oncology Mayo Clinic, Mayo Clinic Cancer Center, Scottsdale, AZ, USA.
authors.forename: Alan H
authors.initials: AH
authors.lastname: Bryce
authors.affiliation: Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
authors.forename: Jean-Pierre A
authors.initials: JA
authors.lastname: Kocher
keywords: Annotation and pathway visualization; Data integration; Genomics; Pathway; User interface; Variant interpretation; Visualization