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Application of Visualization Tools to the Analysis of Histopathological Data Enhances Biological Insight and Interpretation

¹ Cogenics, A Division of Clinical Data, Morrisville, North Carolina 27560, USA
² National Center for Toxicogenomics, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA
³ Environmental Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
⁴ Integrated Laboratory Systems, Inc., Research Triangle Park, North Carolina 27709, USA
⁵ Experimental Pathology Laboratories, Inc., Research Triangle Park, NC 27709,USA

Correspondence: Address correspondence to: Edward K. Lobenhofer, Cogenics, a Division of Clinical Data, 100 Perimeter Park, Suite C, Morrisville, NC 27560, USA; e-mail:elobenhofer{at}cogenics.com

Gene expression profiling, metabolomic screens, and other high-dimensional methods have become an integral part of many biological investigations. To facilitate interpretation of these data, it is important to have detailed phenotypic data—including histopathology—to which these data can be associated, or anchored. However, as the amount of phenotypic data increases, associations within and across these data can be difficult to visualize and interpret. We have developed an approach for categorizing and clustering biologically related histopathological diagnoses to facilitate their visualization, thereby increasing the possibility of identifying associations and facilitating the comparison with other data streams. In this study, we utilize histopathological data generated as part of a standardized toxicogenomics compendium study to generate composite histopathological scores and to develop visualizations that facilitate biological insight. The validity of this approach is illustrated by the identification of transcripts that correlate with the pathology diagnoses that comprise the categories of "response to hepatocellular injury" and "repair." This approach is broadly applicable to studies in which histopathology is used to phenotypically anchor other data, and results in visualizations that facilitate biological interpretation and the identification of associations and relationships within the data.

Key Words: Information visualization • phenotypic anchor • histopathology • gene expression • acute hepatocyte toxicity

Abbreviations: ANOVA, analysis of variance • BW, body weight • cRNA, complementary ribonucleic acid • mg/kg, milligrams per kilogram • PBS, phosphate-buffered saline • PCA, principal component analysis • p.o., per os • PWG, pathology working group • RNA, ribonucleic acid

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