Datgan: A Software for Analyzing Glaucoma Data
Author Information
Author(s): Gareth R. Howell, David O. Walton, Benjamin L. King, Richard T. Libby, Simon W. M. John
Primary Institution: The Howard Hughes Medical Institute
Hypothesis
Can a new software platform improve the analysis of complex transcription profiling datasets for glaucoma?
Conclusion
Datgan provides user-friendly access to complex glaucoma datasets, enhancing understanding of the disease.
Supporting Evidence
- Datgan allows simultaneous querying of multiple genes across different datasets.
- Hierarchical clustering was used to identify early molecular stages of glaucoma.
- More than 70 pairwise comparisons were made to identify differentially expressed genes.
Takeaway
Datgan is a tool that helps scientists look at data about glaucoma more easily, so they can understand it better.
Methodology
Datgan was developed using Python scripts to create a web-based platform for visualizing and analyzing gene expression data from a mouse model of glaucoma.
Limitations
The platform may not be suitable for all types of datasets outside of transcription profiling.
Participant Demographics
Data was generated from at least 50 DBA/2J mice, a common model for glaucoma.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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