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- W2159683766 abstract "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.http://public.tgen.org/sqz. Academic/non-profit:available at no cost under a non-open-source license by requesting from the web-site; Binary: available for direct download at no cost. For-Profit: Submit request for for-profit license from the web-site." @default.
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- W2159683766 date "2010-07-06" @default.
- W2159683766 modified "2023-09-26" @default.
- W2159683766 title "G-SQZ: compact encoding of genomic sequence and quality data" @default.
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- W2159683766 doi "https://doi.org/10.1093/bioinformatics/btq346" @default.
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