Difference between revisions of "NovelSeq"
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{{Bioinformatics application | {{Bioinformatics application | ||
|sw summary=A computational framework to discover the content and location of long novel sequence insertions using paired-end sequencing data | |sw summary=A computational framework to discover the content and location of long novel sequence insertions using paired-end sequencing data | ||
| − | |bio domain=Structural variants, InDel | + | |bio domain=Structural variants, InDel discovery |
|bio method=Mapping, Soft Clustering, Combinatorial Optimization, Assembly | |bio method=Mapping, Soft Clustering, Combinatorial Optimization, Assembly | ||
|bio tech=Illumina | |bio tech=Illumina | ||
Revision as of 17:34, 3 February 2011
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Application data |
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| Created by | Iman Hajirasouliha, Fereydoun Hormozdiari, Can Alkan |
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| Biological application domain(s) | Structural variants, InDel discovery |
| Principal bioinformatics method(s) | Mapping, Soft Clustering, Combinatorial Optimization, Assembly |
| Technology | Illumina |
| Created at | Simon Fraser University
University of Washington |
| Maintained? | Yes |
| Input format(s) | DIVET, SAM |
| Output format(s) | FASTA |
| Programming language(s) | C |
| Licence | BSD License |
| Operating system(s) | Unix |
Summary: A computational framework to discover the content and location of long novel sequence insertions using paired-end sequencing data
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Description
A computational framework to discover the content and location of long novel sequence insertions using paired-end sequencing data generated by the next-generation sequencing platforms. Our framework can be built as part of a general sequence analysis pipeline to discover multiple types of genetic variation (SNPs, structural variation, etc.), thus it requires significantly less computational resources than de novo sequence assembly.
Links
- NovelSeq Homepage [ edit link ]
- NovelSeq Related [ edit link ]
- NovelSeq Related [ edit link ]
- NovelSeq Related [ edit link ]
References
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