DocumentCode
1755731
Title
High-Throughput Compression of FASTQ Data with SeqDB
Author
Howison, Mark
Author_Institution
Center for Comput. & Visualization, Brown Univ., Providence, RI, USA
Volume
10
Issue
1
fYear
2013
fDate
Jan.-Feb. 2013
Firstpage
213
Lastpage
218
Abstract
Compression has become a critical step in storing next-generation sequencing (NGS) data sets because of both the increasing size and decreasing costs of such data. Recent research into efficiently compressing sequence data has focused largely on improving compression ratios. Yet, the throughputs of current methods now lag far behind the I/O bandwidths of modern storage systems. As biologists move their analyses to high-performance systems with greater I/O bandwidth, low-throughput compression becomes a limiting factor. To address this gap, we present a new storage model called SeqDB, which offers high-throughput compression of sequence data with minimal sacrifice in compression ratio. It achieves this by combining the existing multithreaded Blosc compressor with a new data-parallel byte-packing scheme, called SeqPack, which interleaves sequence data and quality scores.
Keywords
DNA; biology computing; data compression; interleaved codes; FASTQ; I/O bandwidths; SeqDB; SeqPack; data compression; multithreaded Blosc compressor; next-generation sequencing; quality scores; sequence data interleaving; Arrays; Bandwidth; Bioinformatics; Genomics; Instruction sets; Libraries; Throughput; Compression; FASTQ; data storage; next-generation sequencing; Computational Biology; Data Compression; Databases, Genetic; High-Throughput Nucleotide Sequencing; Sequence Analysis, DNA;
fLanguage
English
Journal_Title
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher
ieee
ISSN
1545-5963
Type
jour
DOI
10.1109/TCBB.2012.160
Filename
6378359
Link To Document