GenomeGraphs: integrated genomic data visualization with R
<p>Abstract</p> <p>Background</p> <p>Biological studies involve a growing number of distinct high-throughput experiments to characterize samples of interest. There is a lack of methods to visualize these different genomic datasets in a versatile manner. In addition, gen...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2009-01-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://www.biomedcentral.com/1471-2105/10/2 |
| Summary: | <p>Abstract</p> <p>Background</p> <p>Biological studies involve a growing number of distinct high-throughput experiments to characterize samples of interest. There is a lack of methods to visualize these different genomic datasets in a versatile manner. In addition, genomic data analysis requires integrated visualization of experimental data along with constantly changing genomic annotation and statistical analyses.</p> <p>Results</p> <p>We developed <it>GenomeGraphs</it>, as an add-on software package for the statistical programming environment R, to facilitate integrated visualization of genomic datasets. <it>GenomeGraphs </it>uses the <it>biomaRt </it>package to perform on-line annotation queries to Ensembl and translates these to gene/transcript structures in viewports of the <it>grid </it>graphics package. This allows genomic annotation to be plotted together with experimental data. <it>GenomeGraphs </it>can also be used to plot custom annotation tracks in combination with different experimental data types together in one plot using the same genomic coordinate system.</p> <p>Conclusion</p> <p><it>GenomeGraphs </it>is a flexible and extensible software package which can be used to visualize a multitude of genomic datasets within the statistical programming environment R.</p> |
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| ISSN: | 1471-2105 |