Prettycloud: Visualizing weighted and grouped genomic context with mathematical curves

Publication Type:
Conference Proceeding
Citation:
2017 2nd IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2017, 2017, pp. 400 - 403
Issue Date:
2017-06-16
Full metadata record
Files in This Item:
Filename Description Size
07951946.pdfPublished version582.13 kB
Adobe PDF
© 2017 IEEE. Biological networks and visualization of the frequent terms in networks offers a key scenario to visualize and link the biological terms, which are representative of the physiological experiment. Plethora of the publications recently using the RNA-Seq has widely elucidated the organismal biology. However, the embedded annotations are dispersed across representative publications and present end-user a cumbersome task of visually looking at annotations files for the over-represented categories. In the present paper, we present an R package for the visualization of the most frequent annotation terms using math curve functions. The developed pack-age allows for the visualization of the abundant terms in clustered way using weighted indices and present the visualization of the abundance of the terms in relation to word size, font and coloring as per the frequency of the observed word, prettycloud is implementegd in R, and is supported on Windows, Linux and MAC OSX, and freely available at https://sourceforge.net/ projects/prettycloud/or http://genome.sdau.edu.cn/research/software/prettycloud.html (Figure 1).
Please use this identifier to cite or link to this item: