The advance of next generation sequencing (NGS) has greatly promoted the research on genomics analysis, hereditary disease diagnosis, food security, etc. This is comparable or superior to other state-of-the-art lossless NGS data compression algorithms. LW-FQZip was evaluated on eight real-world NGS data sets and achieved compression ratios in the range of 0.111-0.201. The three processed data streams are then packed together with some general purpose compression algorithms like LZMA. To handle the short reads, LW-FQZip uses a novel light-weight mapping model to fast map them against external reference sequence(s) and produce concise alignment results for storage. Particularly, well-designed incremental and run-length-limited encoding schemes are utilized to compress the metadata and quality score streams, respectively. The three components of any given input, i.e., metadata, short reads and quality score strings, are first parsed into three data streams in which the redundancy information are identified and eliminated independently. This paper presents a lossless light-weight reference-based compression algorithm namely LW-FQZip to compress FASTQ data.
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