G-SQZ: compact encoding of genomic sequence and quality data.
CONCLUSIONS
Large volumes of data generated by high-throughput sequencing instruments present non-trivial challenges in data storage, content access and transfer. We present G-SQZ, a Huffman coding-based sequencing-reads-specific representation scheme that compresses data without altering the relative order. G-SQZ has achieved from 65% to 81% compression on benchmark datasets, and it allows selective access without scanning and decoding from start. This article focuses on describing the underlying encoding scheme and its software implementation, and a more theoretical problem of optimal compression is out of scope. The immediate practical benefits include reduced infrastructure and informatics costs in managing and analyzing large sequencing data.


BACKGROUND
http://public.tgen.org/sqz. Academic/non-profit:


METHODS
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Tembe
Waibhav
W
Translational Genomics Research Institute, 445 N 5th Street, Phoenix, AZ 85004, USA. wtembe@tgen.org
Lowey
James
J
Suh
Edward
E
D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D044962:Data Compression; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software