We demonstrated VisShare with visualizing an integrated genomic dataset with 74,604 metadata which represents different features referring to Karyotype, CG, CHG, CHH methylation level, repeat density, lncRNA density, and linkage of fusion transcripts of the maize genome. We applied VisShare to generate cross-platform visualizations regarding the dataset and the underlying goal of data analysis. The circular plot shown in Fig. 1b comprises representative genetic visual models including chromosome arrangement, heat maps, scatter, and chords for visualizing the corresponding data to depict the genome-wide patterns and correlations. VisShare simultaneously renders 18,586 ideograms and tremendous associated metadata reflecting with view's interactions. The plot allows users to zoom in/out or drag the scalable canvas and hover on any ideogram for an explicit tip in the web browser and manipulate gestures for comparable correspondences in the native mobile app.
To invalidate the high performances promoted by VisShare, we have conducted a comparative study using a published mRNA-seq dataset . We compared the performance of Web VisShare with canvas-based Chart.js library and the SVG-based D3.js library (Supplementary Note2). Besides, the comparison considering rendering performance between Native VisShare and iOS native controls is yielded out (Supplementary Note3).
Web VisShare: http://dataviz.sciencewall.net/
Mobile VisShare: http://dataviz.sciencewall.net/native
Github Repo: https://github.com/SutaBeacon/dataviz