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ReadDB Provides Efficient Storage for Mapped Short Reads

P Alexander Rolfe12 and David K Gifford1*

Author Affiliations

1 Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA

2 Pathogenica, Inc, 18th Floor, 245 First Street, Cambridge, MA 02142, USA

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BMC Bioinformatics 2011, 12:278  doi:10.1186/1471-2105-12-278

Published: 7 July 2011

Abstract

Background

The advent of high-throughput sequencing has enabled sequencing based measurements of cellular function, with an individual measurement potentially consisting of more than 108 reads. While tools are available for aligning sets of reads to genomes and interpreting the results, fewer tools have been developed to address the storage and retrieval requirements of large collections of aligned datasets. We present ReadDB, a network accessible column store database system for aligned high-throughput read datasets.

Results

ReadDB stores collections of aligned read positions and provides a client interface to support visualization and analysis. ReadDB is implemented as a network server that responds to queries on genomic intervals in an experiment with either the set of contained reads or a histogram based interval summary. Tests on datasets ranging from 105 to 108 reads demonstrate that ReadDB performance is generally within a factor of two of local-storage based methods and often three to five times better than other network-based methods.

Conclusions

ReadDB is a high-performance foundation for ChIP-Seq and RNA-Seq analysis. The client-server model provides convenient access to compute cluster nodes or desktop visualization software without requiring a shared network filesystem or large amounts of local storage. The client code provides a simple interface for fast data access to visualization or analysis. ReadDB provides a new way to store genome-aligned reads for use in applications where read sequence and alignment mismatches are not needed.