BactoGeNIE: A large-scale comparative genome visualization for big displays
Abstract
The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE through a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. In conclusion, BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.
- Authors:
-
- Univ. of Illinois, Chicago, IL (United States)
- Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Hawai'i at Manoa, Honolulu, HI (United States)
- Univ. of Hawai'i at Manoa, Honolulu, HI (United States)
- Publication Date:
- Research Org.:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Org.:
- USDOE; National Science Foundation (NSF)
- OSTI Identifier:
- 1261160
- Grant/Contract Number:
- CNS-0959053; OCI-0943559; NSF CAREER IIS-1541277
- Resource Type:
- Accepted Manuscript
- Journal Name:
- BMC Bioinformatics
- Additional Journal Information:
- Journal Volume: 16; Journal Issue: Suppl 11; Journal ID: ISSN 1471-2105
- Publisher:
- BioMed Central
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; 97 MATHEMATICS AND COMPUTING; comparative Genomics; large displays; visualization
Citation Formats
Aurisano, Jillian, Reda, Khairi, Johnson, Andrew, Marai, Elisabeta G., and Leigh, Jason. BactoGeNIE: A large-scale comparative genome visualization for big displays. United States: N. p., 2015.
Web. doi:10.1186/1471-2105-16-s11-s6.
Aurisano, Jillian, Reda, Khairi, Johnson, Andrew, Marai, Elisabeta G., & Leigh, Jason. BactoGeNIE: A large-scale comparative genome visualization for big displays. United States. https://doi.org/10.1186/1471-2105-16-s11-s6
Aurisano, Jillian, Reda, Khairi, Johnson, Andrew, Marai, Elisabeta G., and Leigh, Jason. Thu .
"BactoGeNIE: A large-scale comparative genome visualization for big displays". United States. https://doi.org/10.1186/1471-2105-16-s11-s6. https://www.osti.gov/servlets/purl/1261160.
@article{osti_1261160,
title = {BactoGeNIE: A large-scale comparative genome visualization for big displays},
author = {Aurisano, Jillian and Reda, Khairi and Johnson, Andrew and Marai, Elisabeta G. and Leigh, Jason},
abstractNote = {The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE through a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. In conclusion, BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.},
doi = {10.1186/1471-2105-16-s11-s6},
journal = {BMC Bioinformatics},
number = Suppl 11,
volume = 16,
place = {United States},
year = {Thu Aug 13 00:00:00 EDT 2015},
month = {Thu Aug 13 00:00:00 EDT 2015}
}
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