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Hadoop-BAM: Directly Manipulating Next Generation Sequencing Data in the Cloud

Overview
Journal Bioinformatics
Publisher Oxford University Press
Specialty Biology
Date 2012 Feb 4
PMID 22302568
Citations 39
Authors
Matti Niemenmaa
Aleksi Kallio
Andre Schumacher
Petri Klemela
Eija Korpelainen
Keijo Heljanko
Affiliations
Soon will be listed here.
Abstract

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.

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