Bioinformatic insights from metagenomics through visualization.
Cutting-edge biological and bioinformatics research seeks a systems perspective through the analysis of multiple types of high-throughput and other experimental data for the same sample. Systems-level analysis requires the integration and fusion of such data, typically through advanced statistics and mathematics. Visualization is a complementary computational approach that supports integration and analysis of complex data or its derivatives. We present a bioinformatics visualization prototype, Juxter, which depicts categorical information derived from or assigned to these diverse data for the purpose of comparing patterns across categorizations. The visualization allows users to easily discern correlated and anomalous patterns in the data. These patterns, which might not be detected automatically by algorithms, may reveal valuable information leading to insight and discovery. We describe the visualization and interaction capabilities and demonstrate its utility in a new field, metagenomics, which combines molecular biology and genetics to identify and characterize genetic material from multi-species microbial samples.
Havre
Susan L
SL
Pacific Northwest National Laboratory. susan.havre@pnl.gov
Webb-Robertson
Bobbie-Jo
BJ
Shah
Anuj
A
Posse
Christian
C
Gopalan
Banu
B
Brockman
Fred J
FJ
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D003628:Database Management Systems; D030541:Databases, Genetic; D023281:Genomics / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome / Q000145:classification / Q000502:physiology*; D012984:Software; D014584:User-Computer Interface
D020543:Proteome