Hadoop
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The open source Apache Hadoop project, which adopts the MapReduce framework and a distributed file system, has recently given bioinformatics researchers an opportunity to achieve scalable, efficient and reliable computing performance on Linux clusters and on cloud computing services.
Survey of MapReduce frame operation in bioinformatics [1].
List of Hadoop applications for NGS
Hadoop MapReduce-based approaches have become increasingly popular due to their scalability in processing large sequencing data sets[2].
| Tool, Ref | Description | URL |
|---|---|---|
| SeqPig [2] | A library and a collection of tools to manipulate, analyze and query sequencing data sets in a scalable and simple manner.
SeqPig scripts use the Hadoop-based distributed scripting engine Apache Pig, which automatically parallelizes and distributes data processing tasks. |
http://sourceforge.net/projects/seqpig/
http://seqpig.sourceforge.net/ (manual) |
| BioPig [3] | BioPig is based on the Apache's Hadoop MapReduce system and the Pig data flow language. | https://sites.google.com/a/lbl.gov/biopig/ |
| DistMap [4] | A modular, scalable and integrated workflow to map reads in the Hadoop distributed computing framework.
It accepts reads in FASTQ format as input and provides mapped reads in a SAM/BAM format. DistMap supports both paired-end and single-end reads thereby allowing the mapping of read data produced by different sequencing platforms. Currently, DistMap supports 9 mappers:
|
http://code.google.com/p/distmap/ |
References
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