Genomes of hundreds of species have been sequenced to date and many more are being sequenced. As more and more sequence data sets become available, and as the challenge of comparing these massive "billion basepair DNA sequences" becomes substantial, so does the need for more powerful tools supporting the exploration of these data sets. Similarity score data used to compare aligned DNA sequences is inherently one-dimensional. One-dimensional (1D) representations of these data sets do not effectively utilize screen real estate. We present a technique to arrange 1D data in 3D space to allow us to apply state-of-the-art interactive volume visualization techniques for data exploration. We provide results for aligned DNA sequence data and compare it with traditional 1D line plots. Our technique, coupled with 1D line plots, results in effective multiresolution visualization of very large aligned sequence data sets.

Background: Recent advances in sequencing technologies promise to provide a better understanding of the genetics of human disease as well as the evolution of microbial populations. Single Nucleotide Polymorphisms ( SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With today's technological capabilities, it has become possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease in an attempt to identify causative mutations. In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmental samples enables more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at http://genome.lbl.gov/vista/ snpvista[ 1]. Results: We have developed and present two modifications of an interactive visualization tool, SNP-VISTA, to aid in the analyses of the following types of data: A. Large-scale re-sequence data of disease-related genes for discovery of associated and/or causative alleles (GeneSNP-VISTA). B. Massive amounts of ecogenomics data for studying homologous recombination in microbial populations ( EcoSNP-VISTA). The main features and capabilities of SNP-VISTA are: 1) mapping of SNPs to gene structure; 2) classification of SNPs, based on their location in the gene, frequency of occurrence in samples and allele composition; 3) clustering, based on user-defined subsets of SNPs, highlighting haplotypes as well as recombinant sequences; 4) integration of protein evolutionary conservation visualization; and 5) display of automatically calculated recombination points that are user-editable. Conclusion: The main strength of SNP-VISTA is its graphical interface and use of visual representations, which support interactive exploration and hence better understanding of large-scale SNP data by the user.

Recent advances in sequencing technologies promise better diagnostics for many diseases as well as better understanding of evolution of microbial populations. Single Nucleotide Polymorphisms (SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With today's technological capabilities, it is possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease and then screen for causative mutations. In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmental samples makes possible more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at http://genome.lbl.gov/vista/snpvista.

We have developed Phylo-VISTA (Shah et al., 2003), an interactive software tool for analyzing multiple alignments by visualizing a similarity measure for DNA sequences of multiple species. The complexity of visual presentation is effectively organized using a framework based upon inter-species phylogenetic relationships. The phylogenetic organization supports rapid, user-guided inter-species comparison. To aid in navigation through large sequence datasets, Phylo-VISTA provides a user with the ability to select and view data at varying resolutions. The combination of multi-resolution data visualization and analysis, combined with the phylogenetic framework for inter-species comparison, produces a highly flexible and powerful tool for visual data analysis of multiple sequence alignments.

Motivation. The power of multi-sequence comparison for biological discovery is well established and sequence data from a growing list of organisms is becoming available. Thus, a need exists for computational strategies to visually compare multiple aligned sequences to support conservation analysis across various species. To be efficient these visualization algorithms require the ability to universally handle a wide range of evolutionary distances while taking into account phylogeny Results. We have developed Phylo-VISTA, an interactive tool for analyzing multiple alignments by visualizing the similarity of DNA sequences among multiple species while considering their phylogenic relationships. Features include a broad spectrum of resolution parameters for examining the alignment and the ability to easily compare any subtree of sequences within a complete alignment dataset. Phylo-VISTA uses VISTA concepts that have been successfully applied previously to a wide range of comparative genomics data analysis problems. Availability Phylo-VISTA is an interactive java applet available for downloading at http://graphics.cs.ucdavis.edu/~;nyshah/Phylo-VISTA. It is also available on-line at http://www-gsd.lbl.gov/phylovista and is integrated with the global alignment program LAGAN at http://lagan.stanford.edu.Contactphylovista@lbl.gov