Difference between revisions of "CloudBurst"
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|sw summary=CloudBurst is a parallel read-mapping algorithm optimized for mapping next-generation sequence data to the human genome and other reference genomes. | |sw summary=CloudBurst is a parallel read-mapping algorithm optimized for mapping next-generation sequence data to the human genome and other reference genomes. | ||
|bio domain=SNP discovery, Genotyping, Personal genomics | |bio domain=SNP discovery, Genotyping, Personal genomics | ||
| − | |bio method=Mapping, MapReduce, Hadoop, | + | |bio method=Mapping, MapReduce, Hadoop, |
|created by=Schatz MC | |created by=Schatz MC | ||
|created at=University of Maryland | |created at=University of Maryland | ||
| + | |maintained=No | ||
|sw feature=parallel execution, Hadoop, Academic Cloud Computing Initiative | |sw feature=parallel execution, Hadoop, Academic Cloud Computing Initiative | ||
|language=Java, | |language=Java, | ||
}} | }} | ||
| − | + | CloudBurst is a new parallel read-mapping algorithm optimized for mapping next-generation sequence data to the human genome and other reference genomes, for use in a variety of biological analyses including SNP discovery, genotyping, and personal genomics. It is modeled after the short read mapping program [[RMAP]], and reports either all alignments or the unambiguous best alignment for each read with any number of mismatches or differences. This level of sensitivity could be prohibitively time consuming, but CloudBurst uses the open-source Hadoop implementation of MapReduce to parallelize execution using multiple compute nodes. | |
| − | CloudBurst is a new parallel read-mapping algorithm optimized for mapping next-generation sequence data to the human genome and other reference genomes, for use in a variety of biological analyses including SNP discovery, genotyping, and personal genomics. It is modeled after the short read mapping program [[RMAP]], and reports either all alignments or the unambiguous best alignment for each read with any number of mismatches or differences. This level of sensitivity could be prohibitively time consuming, but CloudBurst uses the open-source Hadoop implementation of MapReduce to parallelize execution using multiple compute nodes. | ||
| − | |||
{{Links}} | {{Links}} | ||
{{References}} | {{References}} | ||
| + | {{Link box}} | ||
Revision as of 11:31, 20 August 2013
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Application data |
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| Created by | Schatz MC |
|---|---|
| Biological application domain(s) | SNP discovery, Genotyping, Personal genomics |
| Principal bioinformatics method(s) | Mapping, MapReduce, Hadoop |
| Created at | University of Maryland |
| Maintained? | No |
| Software features | parallel execution, Hadoop, Academic Cloud Computing Initiative |
| Programming language(s) | Java |
Summary: CloudBurst is a parallel read-mapping algorithm optimized for mapping next-generation sequence data to the human genome and other reference genomes.
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CloudBurst is a new parallel read-mapping algorithm optimized for mapping next-generation sequence data to the human genome and other reference genomes, for use in a variety of biological analyses including SNP discovery, genotyping, and personal genomics. It is modeled after the short read mapping program RMAP, and reports either all alignments or the unambiguous best alignment for each read with any number of mismatches or differences. This level of sensitivity could be prohibitively time consuming, but CloudBurst uses the open-source Hadoop implementation of MapReduce to parallelize execution using multiple compute nodes.
Links
References
To add a reference for CloudBurst, enter the PubMed ID in the field below and click 'Add'.
Search for "CloudBurst" in the SEQanswers forum / BioStar or:
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