Difference between revisions of "MagicViewer"
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{{Bioinformatics application | {{Bioinformatics application | ||
| − | |sw summary= | + | |sw summary=Provides a user-friendly interface in which large-scale short reads and sequencing depth can be easily visualized in zoomable images under user definable color scheme through an operating system-independent manner with the implement of Java language. Meanwhile, it holds a versatile genetic variation annotation, filtration and visualization interface, providing details of query options, functional classifications, subset selection, sequence association and primer design. |
| − | |bio domain= | + | |bio domain=De novo sequencing, targeted resequencing and transcriptome sequencing |
| − | |bio method=Visualization, | + | |bio method=Visualization, genetic variation annotation |
|bio tech=Solexa | |bio tech=Solexa | ||
|created by=Jinyu Wu | |created by=Jinyu Wu | ||
|created at=Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China | |created at=Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China | ||
|maintained=Yes | |maintained=Yes | ||
| − | |input format= | + | |input format=A reference genome sequence in fasta format, a sorted bam file containing the aligned short reads obtained from SAMtools and an optional reference genome annotation file in GFF format. |
| − | |sw feature= | + | |sw feature=Holds great promise to easily visualize the short reads alignment, identify the genetic variation and associate them with the annotation information of reference genome. |
|language=Java programming language | |language=Java programming language | ||
| − | |os= | + | |os=In a standalone, operating system-independent manner |
}} | }} | ||
| + | As an integrated solution, MagicViewer can serve as a visualization tool to display large-scale reads, which featured with operating system-independence, user-friendly interface, multiple navigation, zoom mode and custom color schemes. Another predominate feature of MagicViewer is that it provides details of query options for users to identify, filter and annotate the genetic variation between large-scale short reads and reference genomes. | ||
Revision as of 04:57, 3 January 2010
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Application data |
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| Created by | Jinyu Wu |
|---|---|
| Biological application domain(s) | De novo sequencing, targeted resequencing and transcriptome sequencing |
| Principal bioinformatics method(s) | Visualization, genetic variation annotation |
| Technology | Solexa |
| Created at | Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China |
| Maintained? | Yes |
| Input format(s) | A reference genome sequence in fasta format, a sorted bam file containing the aligned short reads obtained from SAMtools and an optional reference genome annotation file in GFF format. |
| Software features | Holds great promise to easily visualize the short reads alignment, identify the genetic variation and associate them with the annotation information of reference genome. |
| Programming language(s) | Java programming language |
| Operating system(s) | In a standalone, operating system-independent manner |
Summary: Provides a user-friendly interface in which large-scale short reads and sequencing depth can be easily visualized in zoomable images under user definable color scheme through an operating system-independent manner with the implement of Java language. Meanwhile, it holds a versatile genetic variation annotation, filtration and visualization interface, providing details of query options, functional classifications, subset selection, sequence association and primer design.
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As an integrated solution, MagicViewer can serve as a visualization tool to display large-scale reads, which featured with operating system-independence, user-friendly interface, multiple navigation, zoom mode and custom color schemes. Another predominate feature of MagicViewer is that it provides details of query options for users to identify, filter and annotate the genetic variation between large-scale short reads and reference genomes.
