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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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Example of the trackCorrelate function to help visualize splice variants. RefSeq and other mRNAs from the human gene BRCA1 are shown aligned to the genome (a) and after compressing introns (b). After compression, it is much easier to see the different isoforms and, for example, discover that mRNAs BC072418.1 and AF005068.1 are not represented among the RefSeqs.
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Figure 2: Example of the trackCorrelate function to help visualize splice variants. RefSeq and other mRNAs from the human gene BRCA1 are shown aligned to the genome (a) and after compressing introns (b). After compression, it is much easier to see the different isoforms and, for example, discover that mRNAs BC072418.1 and AF005068.1 are not represented among the RefSeqs.

Mentions: lwgv runs as a web-based CGI program. Genome features are represented as color-coded tracks on a web browser, and detailed information about each feature can be shown by "mousing-over" them (Figure 1). These features are described in a text-file written in a simple descriptive language. In addition, we offer translators that accept standard annotation formats including BED, WIG, PSL, GFF, and GenBank. Each track, or feature within a track, can have its own unique color, and features across tracks can have lines connecting them to show, for example, the boundaries of homologous sequences across two species or to compare alternative splice sites (Figure 2). In addition to tracks, the sequence viewer can represent numerical information along a genome using line plots, smooth line plots (using cubic splines), or histograms. Basic properties like image width, track height, and navigation buttons are all configurable. Commonly used feature sets and configuration parameters can be stored in separate files and included into an annotation file with an "#include" statement to prevent regenerating the same features in contexts where only part of the analysis data is dynamic.


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

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

Example of the trackCorrelate function to help visualize splice variants. RefSeq and other mRNAs from the human gene BRCA1 are shown aligned to the genome (a) and after compressing introns (b). After compression, it is much easier to see the different isoforms and, for example, discover that mRNAs BC072418.1 and AF005068.1 are not represented among the RefSeqs.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 2: Example of the trackCorrelate function to help visualize splice variants. RefSeq and other mRNAs from the human gene BRCA1 are shown aligned to the genome (a) and after compressing introns (b). After compression, it is much easier to see the different isoforms and, for example, discover that mRNAs BC072418.1 and AF005068.1 are not represented among the RefSeqs.
Mentions: lwgv runs as a web-based CGI program. Genome features are represented as color-coded tracks on a web browser, and detailed information about each feature can be shown by "mousing-over" them (Figure 1). These features are described in a text-file written in a simple descriptive language. In addition, we offer translators that accept standard annotation formats including BED, WIG, PSL, GFF, and GenBank. Each track, or feature within a track, can have its own unique color, and features across tracks can have lines connecting them to show, for example, the boundaries of homologous sequences across two species or to compare alternative splice sites (Figure 2). In addition to tracks, the sequence viewer can represent numerical information along a genome using line plots, smooth line plots (using cubic splines), or histograms. Basic properties like image width, track height, and navigation buttons are all configurable. Commonly used feature sets and configuration parameters can be stored in separate files and included into an annotation file with an "#include" statement to prevent regenerating the same features in contexts where only part of the analysis data is dynamic.

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