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

123Citations
Citations of this article
210Readers
Mendeley users who have this article in their library.

This article is free to access.

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. © The Author(s) 2012. Published by Oxford University Press.

Cite

CITATION STYLE

APA

Niemenmaa, M., Kallio, A., Schumacher, A., Klemelä, P., Korpelainen, E., & Heljanko, K. (2012). Hadoop-BAM: Directly manipulating next generation sequencing data in the cloud. Bioinformatics, 28(6), 876–877. https://doi.org/10.1093/bioinformatics/bts054

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free