Difference between revisions of "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. | 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. | ||
Revision as of 02:56, 17 November 2013
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) |
| Hadoop-BAM [3] | Hadoop-BAM is a Java library for the manipulation of files in common bioinformatics formats using the Hadoop MapReduce framework with the Picard SAM JDK, and command line tools similar to SAMtools.
The file formats currently supported are BAM, SAM, FASTQ, FASTA, QSEQ, BCF, and VCF. SeqPig project provides a higher-level interface to the file formats supported by Hadoop-BAM |
http://sourceforge.net/projects/hadoop-bam/ |
| BioPig [4] | 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 [5] | 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/ |
| Eoulsan [6] | Eoulsan provides an integrated and flexible solution for RNA-Seq data analysis of differential expression.
Amazon EC2, Java |
http://transcriptome.ens.fr/eoulsan/ |
| FX [7] | FX is an RNA-Seq analysis tool, which runs in parallel on cloud computing infrastructure, for the estimation of gene expression levels and genomic variant calling.
Input:
Output
Amazon EC2, Java |
http://fx.gmi.ac.kr |
| Biodoop | Current applications focus on sequence alignment and manipulation of alignment records. Applications generally run on the Pydoop API for Hadoop.
Currently, Biodoop’s core contains a few modules for handling FASTA streams, wrappers for BLAST, I/O modules for some bio formats, a module for converting sequences to the nib format and protobuf serializers for several objects. |
http://biodoop.sourceforge.net/core/ |
| Seal | Seal is a suite of distributed applications for aligning short DNA reads, and manipulating and analyzing short read alignments.
Currently it includes tools for: read demultiplexing, read alignment, duplicate read removal, sorting read mappings, and calculating statistics for empirical base quality recalibration. Seal is part of the Biodoop suite of tools. |
http://biodoop-seal.sourceforge.net/ |
| CloudAligner [8] | A fast and full-featured MapReduce based tool for sequence mapping.
One of the first work for Hadoop, the article has a lot of details. Amazon EC2, Java |
http://sourceforge.net/projects/cloudaligner/files/ |
| CloudBurst [9] | A 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.
The first work for Hadoop, the article has a lot of details. |
http://cloudburst-bio.sourceforge.net/ |
| Crossbow [10] | cloud computing tool for identifying SNPs from high-coverage, short-read resequencing data. Two robust tools, Bowtie and SOAPsnp, implement the fundamental alignment and variant calling operations respectively, and have demonstrated capabilities within Crossbow of analyzing approximately one billion short reads per hour on a commodity Hadoop cluster with 320 cores.
Amazon EC2 |
http://bowtie-bio.sourceforge.net/crossbow |
| Myrna[11] | Myrna is a cloud computing tool for calculating differential gene expression in large RNA-seq datasets. Myrna uses Bowtie for short read alignment and R/Bioconductor for interval calculations, normalization, and statistical testing. These tools are combined in an automatic, parallel pipeline that runs in the cloud (Elastic MapReduce in this case) on a local Hadoop cluster, or on a single computer, exploiting multiple computers and CPUs wherever possible. | http://bowtie-bio.sf.net/myrna |
| BlueSNP [12] | R package which distributes GWAS computation over a cluster configured with the Hadoop framework, making computationally intensive analyses, such as estimating empirical p-values via data permutation, and searching for expression quantitative trait loci over thousands of genes, feasible for large genotype-phenotype datasets.
It uses RHIPE R package (http://www.datadr.org) for authoring and running MapReduce programs from within the R environment. |
http://github.com/ibm-bioinformatics/bluesnp |
References
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