Sybil: Methods and Software for Multiple Genome Comparison and Visualization
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With the successful completion of genome sequencing projects for a variety of model organisms, the selection of candidate
organisms for future sequencing efforts has been guided increasingly by a desire to enable comparative genomics. This trend
has both depended on and encouraged the development of software tools that can elucidate and capitalize on the similarities
and differences between genomes. “Sybil,” one such tool, is a primarily web-based software package whose primary goal is to
facilitate the analysis and visualization of comparative genome data, with a particular emphasis on protein and gene cluster
data. Herein, a two-phase protein clustering algorithm, used to generate protein clusters suitable for analysis through Sybil
and a method for creating graphical displays of protein or gene clusters that span multiple genomes are described. When combined,
these two relatively simple techniques provide the user of the Sybil software (The Institute for Genomic Research [TIGR] Bioinformatics
Department) with a browsable graphical display of his or her “input” genomes, showing which genes are conserved based on the
parameters supplied to the protein clustering algorithm. For any given protein cluster the graphical display consists of a
local alignment of the genomes in which the clustered genes are located. The genomes are arranged in a vertical stack, as
in a multiple alignment, and shaded areas are used to connect genes in the same cluster, thus displaying conservation at the
protein level in the context of the underlying genomic sequences. The authors have found this display—and slight variants
thereof—useful for a variety of annotation and comparison tasks, ranging from identifying “missed” gene models or single-exon
discrepancies between orthologous genes, to finding large or small regions of conserved gene synteny, and investigating the
properties of the breakpoints between such regions.
Book Title: Gene Function Analysis
Series: Methods in Molecular Biology | Volume: 408 | Pub. Date: Aug-23-2007 | Page Range: 93-108 | DOI: 10.1007/978-1-59745-547-3_6
Subject: Genetics/Genomics
Key Words: Bioinformatics - Bioperl - comparative genomics - ortholog - paralog - protein clustering - visualization
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