Application of visualization tools to the analysis of histopathological data enhances biological insight and interpretation
| Autor: | Patrick Hurban, Gary A. Boorman, K. L. Phillips, David E. Malarkey, Christopher D. Houle, Pamela E. Blackshear, Alexandra N. Heinloth, Edward K. Lobenhofer |
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| Rok vydání: | 2006 |
| Předmět: |
Male
Databases Factual 040301 veterinary sciences Computational biology Biology Toxicology Bioinformatics 030226 pharmacology & pharmacy Toxicogenetics Pathology and Forensic Medicine 0403 veterinary science 03 medical and health sciences Information visualization Necrosis 0302 clinical medicine Pathology Animals Regeneration Cluster analysis Molecular Biology Hyperplasia Data stream mining business.industry Gene Expression Profiling 04 agricultural and veterinary sciences Cell Biology Compendium Rats Inbred F344 Visualization Rats Gene expression profiling Liver Hepatocytes Identification (biology) business Toxicogenomics |
| Zdroj: | Toxicologic pathology. 34(7) |
| ISSN: | 0192-6233 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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