DataMap: A Portable Application for Visualizing High-Dimensional Data
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866909576403615744 |
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| author | Ge, Xijin |
| author_facet | Ge, Xijin |
| contents | Motivation: The visualization and analysis of high-dimensional data are essential in biomedical research. There is a need for secure, scalable, and reproducible tools to facilitate data exploration and interpretation. Results: We introduce DataMap, a browser-based application for visualization of high-dimensional data using heatmaps, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE). DataMap runs in the web browser, ensuring data privacy while eliminating the need for installation or a server. The application has an intuitive user interface for data transformation, annotation, and generation of reproducible R code. Availability and Implementation: Freely available as a GitHub page https://gexijin.github.io/datamap/. The source code can be found at https://github.com/gexijin/datamap, and can also be installed as an R package. Contact: Xijin.Ge@sdstate.ed |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_08875 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | DataMap: A Portable Application for Visualizing High-Dimensional Data Ge, Xijin Quantitative Methods Human-Computer Interaction Machine Learning Applications Motivation: The visualization and analysis of high-dimensional data are essential in biomedical research. There is a need for secure, scalable, and reproducible tools to facilitate data exploration and interpretation. Results: We introduce DataMap, a browser-based application for visualization of high-dimensional data using heatmaps, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE). DataMap runs in the web browser, ensuring data privacy while eliminating the need for installation or a server. The application has an intuitive user interface for data transformation, annotation, and generation of reproducible R code. Availability and Implementation: Freely available as a GitHub page https://gexijin.github.io/datamap/. The source code can be found at https://github.com/gexijin/datamap, and can also be installed as an R package. Contact: Xijin.Ge@sdstate.ed |
| title | DataMap: A Portable Application for Visualizing High-Dimensional Data |
| topic | Quantitative Methods Human-Computer Interaction Machine Learning Applications |
| url | https://arxiv.org/abs/2504.08875 |