Hadoop-BAM: directly manipulating next generation sequencing data in the cloud. - National Genomics Data Center (CNCB-NGDC)

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Hadoop-BAM: directly manipulating next generation sequencing data in the cloud.

Matti Niemenmaa, Aleksi Kallio, André Schumacher, Petri Klemelä, Eija Korpelainen, Keijo Heljanko

Author Information

Matti Niemenmaa: Aalto University, Department of Information and Computer Science, Aalto, Finland. matti.niemenmaa@aalto.fi

PMID: 22302568 DOI: 10.1093/bioinformatics/bts054

Hadoop-BAM is a novel library for the scalable manipulation of aligned next-generation sequencing data in the Hadoop distributed computing framework. It acts as an integration layer between analysis applications and BAM files that are processed using Hadoop. Hadoop-BAM solves the issues related to BAM data access by presenting a convenient API for implementing map and reduce functions that can directly operate on BAM records. It builds on top of the Picard SAM JDK, so tools that rely on the Picard API are expected to be easily convertible to support large-scale distributed processing. In this article we demonstrate the use of Hadoop-BAM by building a coverage summarizing tool for the Chipster genome browser. Our results show that Hadoop offers good scalability, and one should avoid moving data in and out of Hadoop between analysis steps.

BMC Bioinformatics. 2010 Dec 21;11 Suppl 12:S2 [PMID: 21210981]
Genome Res. 2010 Sep;20(9):1297-303 [PMID: 20644199]
Bioinformatics. 2011 Aug 1;27(15):2159-60 [PMID: 21697132]
BMC Bioinformatics. 2010 Dec 21;11 Suppl 12:S1 [PMID: 21210976]
BMC Genomics. 2011 Oct 14;12:507 [PMID: 21999641]
Bioinformatics. 2009 Aug 15;25(16):2078-9 [PMID: 19505943]

Genome

High-Throughput Nucleotide Sequencing

Sequence Analysis, DNA

Software

User-Computer Interface

Journal Article Research Support, Non-U.S. Gov't

BioCode: BT004317 (Hadoop-BAM)

Are Next-Generation Sequencing Tools Ready for the Cloud?mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud.Next-generation sequencing data analysis.Archiving next generation sequencing data.Sequencing and Reconstructing Helminth Mitochondrial Genomes Directly from Genomic Next-Generation Sequencing Data.NGSNGS: next-generation simulator for next-generation sequencing data.Implementation of Cloud based next generation sequencing data analysis in a clinical laboratory.'Big data', Hadoop and cloud computing in genomics.Bambino: a variant detector and alignment viewer for next-generation sequencing data in the SAM/BAM format.Pathway analysis with next-generation sequencing data.

Biospark: scalable analysis of large numerical datasets from biological simulations and experiments using Hadoop and Spark.SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop.BAMSI: a multi-cloud service for scalable distributed filtering of massive genome data.DECA: scalable XHMM exome copy-number variant calling with ADAM and Apache Spark.ADS-HCSpark: A scalable HaplotypeCaller leveraging adaptive data segmentation to accelerate variant calling on Spark.Shared data science infrastructure for genomics data.A comparison of three programming languages for a full-fledged next-generation sequencing tool.Halvade-RNA: Parallel variant calling from transcriptomic data using MapReduce.Halvade: scalable sequence analysis with MapReduce.Closha: bioinformatics workflow system for the analysis of massive sequencing data.

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