
Visualizing virus population variability from next generation sequencing data
LayerCake is a tool designed to assist in the exploration of the genetic variability of the population of viruses at multiple time points and in multiple individuals, a task that necessitates considering large amounts of sequence data and the quality issues inherent in obtaining such data in a practical manner. This design affords the examination of the amount of variability and mutation at each position in the genome for many populations of viruses. This design contains novel visualization techniques that support this specific class of analysis while addressing the issues of data aggregation, confidence visualization, and interaction support that arise when making use of large amounts of sequence data with variable uncertainty. These techniques generalize to a wide class of visualization problems where confidence is not known a priori, and aggregation in multiple directions is necessary.
Release Date: |
August, 2015 |
Status: | |
Availability: | |
Data type: | |
Techniques: | 2D "confidence fog" technique, deep sequencing method, Focus + Context Zooming |
Software: | Installed |
Technology: | Java |
Platform: | Linux, Mac OSX, Windows |
Requirements: |
Project development
This work was supported by NSF awards IIS-0946598 and CMMI-0941013. Related virology research was supported by NIH R01 AI084787.
Last updated on 9th November, 2016