GateKeeper-GPU：短读段比对中快速且准确的预比对过滤
GateKeeper-GPU: Fast and Accurate Pre-Alignment Filtering in Short Read Mapping
AI总结：
本文提出 GPU 加速的预比对过滤器 GateKeeper-GPU，通过改进 GateKeeper 准确性并利用大规模线程并行筛查序列对，为序列比对带来 2.9 倍加速，并使 mrFAST 端到端运行最高提速 1.4 倍。
摘要：
在短读段定位的最后一步，需要使用序列比对算法验证读段在参考基因组上的候选位置，以计算它们与相应参考片段之间的差异。计算两个序列之间的异同仍然具有很高的计算开销，因为近似字符串匹配技术传统上沿用了具有二次时间和空间复杂度的动态规划算法。我们提出 GateKeeper-GPU，这是一种快速且准确的预比对过滤器，可有效减少对昂贵序列比对的需求。GateKeeper-GPU 有两项主要贡献：第一，提升 GateKeeper（一种轻量级预比对过滤器）的过滤准确性；第二，利用现代 GPU 大量 GPU 线程所提供的大规模并行能力，快速并发地检查大量序列对。通过减少工作量，GateKeeper-GPU 为序列比对提供了 2.9 倍加速，并使综合读段定位器 mrFAST 的端到端执行时间最高加速 1.4 倍。GateKeeper-GPU 可在 https://github.com/BilkentCompGen/GateKeeper-GPU 获取。
英文摘要：
At the last step of short read mapping, the candidate locations of the reads on the reference genome are verified to compute their differences from the corresponding reference segments using sequence alignment algorithms. Calculating the similarities and differences between two sequences is still computationally expensive since approximate string matching techniques traditionally inherit dynamic programming algorithms with quadratic time and space complexity. We introduce GateKeeper-GPU, a fast and accurate pre-alignment filter that efficiently reduces the need for expensive sequence alignment. GateKeeper-GPU provides two main contributions: first, improving the filtering accuracy of GateKeeper (a lightweight pre-alignment filter), and second, exploiting the massive parallelism provided by the large number of GPU threads of modern GPUs to examine numerous sequence pairs rapidly and concurrently. By reducing the work, GateKeeper-GPU provides an acceleration of 2.9x to sequence alignment and up to 1.4x speedup to the end-to-end execution time of a comprehensive read mapper (mrFAST). GateKeeper-GPU is available at https://github.com/BilkentCompGen/GateKeeper-GPU.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
