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Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context.

Faith JJ, Olson AJ, Gardner TS, Sachidanandam R - BMC Bioinformatics (2007)

Bottom Line: Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context.The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context.It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bioinformatics Program, Boston University, USA. faith@bu.edu

ABSTRACT

Background: Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal.

Results: lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales.

Conclusion: lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired.

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lwgv is used with the Many Microbe Microarrays Database to allow users to dynamically display expression changes in their chromosomal context. In this example, significant expression changes between E. coli cells grown in rich media and E. coli cells grown in rich media with norfloxacin antibiotic are shown with lwgv. In this chromosomal context, it is immediately clear that several large regions of the genome have significantly changed expression levels between these two conditions. For example, over 28 consecutive genes and intergenic regions related to flagella have a significant fold change (track grp fold). These significantly changed genes are displayed on track sig fold.
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Figure 3: lwgv is used with the Many Microbe Microarrays Database to allow users to dynamically display expression changes in their chromosomal context. In this example, significant expression changes between E. coli cells grown in rich media and E. coli cells grown in rich media with norfloxacin antibiotic are shown with lwgv. In this chromosomal context, it is immediately clear that several large regions of the genome have significantly changed expression levels between these two conditions. For example, over 28 consecutive genes and intergenic regions related to flagella have a significant fold change (track grp fold). These significantly changed genes are displayed on track sig fold.

Mentions: Common microarray analysis procedures yield lists of genes, whose expression changes significantly in response to an environmental or genetic perturbation. The functional role for most of these expression changes is typically unknown, and the often-large number of changed genes hinders human interpretation of their role. In many species, genes with similar functional roles often exhibit chromosomal proximity and therefore operate as a co-expressed module, even when part of distinct operons and transcription units [16,17]. To facilitate the sharing, discovery, and analysis of expression data in a genome localization context, we created an lwgv application where users can dynamically choose any two sets of microarray experiments in M3D and view gene expression changes in their chromosomal context (Figure 3). M3D includes Affymetrix microarray compendia for multiple microbes including S. oneidensis, E. coli, and S. cerevisiae, and it also provides visualization and data download tools [18,19]. lwgv is also packaged with a script that allows any expression data in the commonly used GPR format to be visualized in a genome context.


Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context.

Faith JJ, Olson AJ, Gardner TS, Sachidanandam R - BMC Bioinformatics (2007)

lwgv is used with the Many Microbe Microarrays Database to allow users to dynamically display expression changes in their chromosomal context. In this example, significant expression changes between E. coli cells grown in rich media and E. coli cells grown in rich media with norfloxacin antibiotic are shown with lwgv. In this chromosomal context, it is immediately clear that several large regions of the genome have significantly changed expression levels between these two conditions. For example, over 28 consecutive genes and intergenic regions related to flagella have a significant fold change (track grp fold). These significantly changed genes are displayed on track sig fold.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2238324&req=5

Figure 3: lwgv is used with the Many Microbe Microarrays Database to allow users to dynamically display expression changes in their chromosomal context. In this example, significant expression changes between E. coli cells grown in rich media and E. coli cells grown in rich media with norfloxacin antibiotic are shown with lwgv. In this chromosomal context, it is immediately clear that several large regions of the genome have significantly changed expression levels between these two conditions. For example, over 28 consecutive genes and intergenic regions related to flagella have a significant fold change (track grp fold). These significantly changed genes are displayed on track sig fold.
Mentions: Common microarray analysis procedures yield lists of genes, whose expression changes significantly in response to an environmental or genetic perturbation. The functional role for most of these expression changes is typically unknown, and the often-large number of changed genes hinders human interpretation of their role. In many species, genes with similar functional roles often exhibit chromosomal proximity and therefore operate as a co-expressed module, even when part of distinct operons and transcription units [16,17]. To facilitate the sharing, discovery, and analysis of expression data in a genome localization context, we created an lwgv application where users can dynamically choose any two sets of microarray experiments in M3D and view gene expression changes in their chromosomal context (Figure 3). M3D includes Affymetrix microarray compendia for multiple microbes including S. oneidensis, E. coli, and S. cerevisiae, and it also provides visualization and data download tools [18,19]. lwgv is also packaged with a script that allows any expression data in the commonly used GPR format to be visualized in a genome context.

Bottom Line: Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context.The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context.It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bioinformatics Program, Boston University, USA. faith@bu.edu

ABSTRACT

Background: Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal.

Results: lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales.

Conclusion: lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired.

Show MeSH