Visualizing Multidimensional Data with Glyph SPLOMs
Visualizing Multidimensional Data with Glyph SPLOMs
复制标题
使用 Glyph SPLOM 可视化多维数据
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
R. Machiraju
中科院分区：
文献类型：
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作者：
A. Yates;A. Webb;Michael F. Sharpnack;H. Chamberlin;Kun Huang;R. Machiraju
散点图矩阵或SPLOM提供了一种可视化和表示多维数据的可行方法，特别是对于少数维度。对于非常高维的数据，我们引入了一种新的技术来总结一个SPLOM，作为一个集群矩阵的字形，或Glossary SPLOM。每个子图可视地编码依赖强度、距离相关性和基于散点图象限的占用的逻辑依赖类的一般度量。我们在两个例子中提出GlancesSPLOM作为传统的基于相关性的热图和散点图矩阵的一般替代方案：来自世界卫生组织（WHO）的人口统计数据和来自发育生物学的基因表达数据。通过使用依赖类和强度两者，Glencore SPLOM比热图更详细地说明了高维数据，但比SPLOM具有更多的汇总。更重要的是，GlossomSPLOM的总结能力允许断言数据中的“必然性”因果关系，并在各种动态系统中重建交互网络。
Scatterplot matrices or SPLOMs provide a feasible method of visualizing and representing multi‐dimensional data especially for a small number of dimensions. For very high dimensional data, we introduce a novel technique to summarize a SPLOM, as a clustered matrix of glyphs, or a Glyph SPLOM. Each glyph visually encodes a general measure of dependency strength, distance correlation, and a logical dependency class based on the occupancy of the scatterplot quadrants. We present the Glyph SPLOM as a general alternative to the traditional correlation based heatmap and the scatterplot matrix in two examples: demography data from the World Health Organization (WHO), and gene expression data from developmental biology. By using both, dependency class and strength, the Glyph SPLOM illustrates high dimensional data in more detail than a heatmap but with more summarization than a SPLOM. More importantly, the summarization capabilities of Glyph SPLOM allow for the assertion of “necessity” causal relationships in the data and the reconstruction of interaction networks in various dynamic systems.
影响因子：
4.4
作者：
Piccolo, Stephen R.;Sun, Ying;Campbell, Joshua D.;Lenburg, Marc E.;Bild, Andrea H.;Johnson, W. Evan
通讯作者：
Johnson, W. Evan