Analyzing Histone Modifications in iPS Cells Using Tiled Binned 3D Scatter Plots

Zeckzer, Dirk; Gerighausen, Daniel; Müller, Lydia

doi:10.1109/bdva.2016.7787042

Cited by 5 publications

(9 citation statements)

References 20 publications

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“…3D scatterplots are used in various applications for visualizing multidimensional data [37,43,45,65], e.g., to visualize network data [53] or a development over time in space time cubes [17,35]. Sedlmair et al [48] compared 2D scatterplots, 3D scatterplots and scatterplot matrices.…”

Section: D Visualizationsmentioning

confidence: 99%

The Impact of Immersion on Cluster Identification Tasks

Kraus

Weiler

Oelke

et al. 2020

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. A cluster identification task was performed and evaluated in four different visualization design spaces. Two screen-based methods, namely a scatterplot matrix (a) and a 3D scatterplot in a cube (b), and two visualizations in a VR environment: a 3D scatterplot on a virtual table (c) and a room-sized scatterplot (d). Gray lines emphasize transitions between visualization design spaces.Abstract-Recent developments in technology encourage the use of head-mounted displays (HMDs) as a medium to explore visualizations in virtual realities (VRs). VR environments (VREs) enable new, more immersive visualization design spaces compared to traditional computer screens. Previous studies in different domains, such as medicine, psychology, and geology, report a positive effect of immersion, e.g., on learning performance or phobia treatment effectiveness. Our work presented in this paper assesses the applicability of those findings to a common task from the information visualization (InfoVis) domain. We conducted a quantitative user study to investigate the impact of immersion on cluster identification tasks in scatterplot visualizations. The main experiment was carried out with 18 participants in a within-subjects setting using four different visualizations, (1) a 2D scatterplot matrix on a screen, (2) a 3D scatterplot on a screen, (3) a 3D scatterplot miniature in a VRE and (4) a fully immersive 3D scatterplot in a VRE. The four visualization design spaces vary in their level of immersion, as shown in a supplementary study. The results of our main study indicate that task performance differs between the investigated visualization design spaces in terms of accuracy, efficiency, memorability, sense of orientation, and user preference. In particular, the 2D visualization on the screen performed worse compared to the 3D visualizations with regard to the measured variables. The study shows that an increased level of immersion can be a substantial benefit in the context of 3D data and cluster detection.

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Section: D Visualizationsmentioning

confidence: 99%

The Impact of Immersion on Cluster Identification Tasks

Kraus

Weiler

Oelke

et al. 2020

IEEE Trans. Visual. Comput. Graphics

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“…Testing the divisive clustering methods k-means++ [2,17], k-median [13], and even consensus clustering [7,8] in conjunction with clustering assessment strategies and indices like Davies Bouldin Index [6], Hubert Statistics [12], Dunn Index [3], and silhouettes [21] (see also Jain and Dubes [13]) lead to a partitioning of the data with limited expressiveness [9]. Applying the visualization strategies TiBi-SPLOM [28] and TiBi-3D [27] showed why: the characteristics of the data makes the direct application of clustering unsuitable. The data is very noisy.…”

Section: Tibi-cluster-methodologymentioning

confidence: 99%

“…Additionally, visualization as well as interaction facilities are designed following the recommendations from information visualization literature [19,25,26]. The literature provides a set of guidelines any visualization should adhere to (see also Zeckzer et al [27,28]):…”

Section: Goalsmentioning

confidence: 99%

“…Histone modifications are important for the development of the cells regulating the transcription states of genes and thereby their overall expression patterns. The evolution of certain histone modifications plays an important role during the differentiation of cells, e.g., from embryonic stem cells to embryonic fibroblasts or to neural progenitor cells [23,27,28].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, Zeckzer et al proposed tiled binned scatter plot matrices (TiBi-SPLOM) [28] and tiled binned 3D scatter plots (TiBi-3D) [27] fostering analyzing the fate of epigenetic marks during differentiation. While our previous approaches [23,27,28] provide effective and efficient visualizations of histone modification data supporting these intermediate level analyses, there is still room for improvements.…”

Section: Introductionmentioning

confidence: 99%

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Analyzing Histone Modifications Using Tiled Binned Clustering and 3D Scatter Plots

Zeckzer¹,

Wiegreffe

Müller

2018

JWSCG

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A major goal in epigenetics is understanding how cells differentiate into different cell types. Besides the increase of individual data sets, the amount of replicated experiments generating a tremendous amount of data is ever increasing. While biologists primarily analyze their data on the highest level using statistical correlations or on the lowest level analyzing nucleotide sequences, determining the fate of histone modifications during cell specification necessitates improved analysis capabilities on one or more intermediate levels. For this type of analysis, it proved to be very useful to use tiled binned scatter plot matrices showing binary relationships or to use tiled binned 3D scatter plots showing ternary relationships. Quarternary or general n-ary relationships are not easily analyzable using visualization techniques like scatter plots, only. Therefore, we augmented existing clustering methods with the tiling and binning idea enabling the analysis of n-ary relationships. Analyzing the changes of histone modifications comparing two cell lines using tiled binned clustering, we found new, unknown relations in the data.

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