Title | GenAMap: Visualization strategies for structured association mapping |
Publication Type | Conference Paper |
Year of Publication | 2011 |
Authors | Curtis, RE, Kinnaird, P, Xing, EP |
Conference Name | 2011 IEEE Symposium on Biological Data Visualization (BioVis)2011 IEEE Symposium on Biological Data Visualization (BioVis). |
Publisher | IEEE |
Conference Location | Providence, RI, USA |
ISBN Number | 978-1-4673-0003-2 |
Accession Number | 12408400 |
Keywords | Algorithm design and analysis, Bioinformatics, Data visualization, Gene expression, Genomics, Heating |
Abstract | Association mapping studies promise to link DNA mutations to gene expression data, possibly leading to innovative treatments for diseases. One challenge in large-scale association mapping studies is exploring the results of the computational analysis to find relevant and interesting associations. Although many association mapping studies find associations from a genome-wide collection of genomic data to hundreds or thousands of traits, current visualization software only allow these associations to be explored one trait at a time. The inability to explore the association of a genomic location to multiple traits hides the inherent interaction between traits in the analysis. Additionally, researchers must rely on collections of in-house scripts and multiple tools to perform an analysis, adding time and effort to find interesting associations. In this paper, we present a novel visual analytics system called GenAMap. GenAMap replaces the time-consuming analysis of large-scale association mapping studies with exploratory visualization tools that give geneticists an overview of the data and lead them to relevant information. We present the results of a preliminary evaluation that validated our basic approach. |
URL | http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6094052 |
DOI | 10.1109/BioVis.2011.6094052 |
Refereed Designation | Unknown |