Improving Genome Compression Performance by Extending Reference Sequences

XiangDong Ma, Jianhua Chen
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Abstract

We propose an efficient referential genome compression algorithm called RCCG. It extends reference genomes by its reverse complementation and uses coprime window sampling to detect the maximum matches (MEMs) between two genome sequences. After the assessment, those selected matches will be united to form mutation-containing matches (MCMs). The average compression ratio of the proposed algorithm is higher than that of the state-of-the-art genome compression algorithms.
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通过扩展参考序列提高基因组压缩性能
我们提出了一种高效的参考基因组压缩算法RCCG。它通过反向互补来扩展参考基因组,并利用协素窗采样来检测两个基因组序列之间的最大匹配(MEMs)。经过评估后,这些被选中的匹配将被联合起来形成包含突变的匹配(mcm)。该算法的平均压缩比高于目前最先进的基因组压缩算法。
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