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首页> 外文期刊>BMC Genomics >GRIM-Filter: Fast seed location filtering in DNA read mapping using processing-in-memory technologies
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GRIM-Filter: Fast seed location filtering in DNA read mapping using processing-in-memory technologies

机译：GRIM-Filter：使用内存中处理技术在DNA读图中快速进行种子位置过滤

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Seed location filtering is critical in DNA read mapping, a process where billions of DNA fragments (reads) sampled from a donor are mapped onto a reference genome to identify genomic variants of the donor. State-of-the-art read mappers 1) quickly generate possible mapping locations for seeds (i.e., smaller segments) within each read, 2) extract reference sequences at each of the mapping locations, and 3) check similarity between each read and its associated reference sequences with a computationally-expensive algorithm (i.e., sequence alignment) to determine the origin of the read. A seed location filter comes into play before alignment, discarding seed locations that alignment would deem a poor match. The ideal seed location filter would discard all poor match locations prior to alignment such that there is no wasted computation on unnecessary alignments. We propose a novel seed location filtering algorithm, GRIM-Filter, optimized to exploit 3D-stacked memory systems that integrate computation within a logic layer stacked under memory layers, to perform processing-in-memory (PIM). GRIM-Filter quickly filters seed locations by 1) introducing a new representation of coarse-grained segments of the reference genome, and 2) using massively-parallel in-memory operations to identify read presence within each coarse-grained segment. Our evaluations show that for a sequence alignment error tolerance of 0.05, GRIM-Filter 1) reduces the false negative rate of filtering by 5.59x–6.41x, and 2) provides an end-to-end read mapper speedup of 1.81x–3.65x, compared to a state-of-the-art read mapper employing the best previous seed location filtering algorithm. GRIM-Filter exploits 3D-stacked memory, which enables the efficient use of processing-in-memory, to overcome the memory bandwidth bottleneck in seed location filtering. We show that GRIM-Filter significantly improves the performance of a state-of-the-art read mapper. GRIM-Filter is a universal seed location filter that can be applied to any read mapper. We hope that our results provide inspiration for new works to design other bioinformatics algorithms that take advantage of emerging technologies and new processing paradigms, such as processing-in-memory using 3D-stacked memory devices.
机译：种子位置过滤对于DNA读取作图至关重要，在该过程中，将从供体中取样的数十亿个DNA片段（读物）映射到参考基因组上，以鉴定供体的基因组变异。最新的阅读器1）快速生成每次阅读中种子（即较小片段）的可能映射位置，2）在每个映射位置提取参考序列，3）检查每个阅读与其序列之间的相似性将相关的参考序列与计算昂贵的算法（即序列比对）相关联，以确定读取的来源。种子位置过滤器在对齐之前开始起作用，丢弃那些认为对齐不佳的种子位置。理想的种子位置过滤器将在对齐之前丢弃所有较差的匹配位置，从而不会在不必要的对齐上浪费计算。我们提出了一种新颖的种子位置过滤算法GRIM-Filter，该算法经过优化以利用3D堆栈存储系统，该系统将计算集成在存储层下面的逻辑层中，以执行内存处理（PIM）。 GRIM-Filter通过1）引入参考基因组粗粒区段的新表示形式和2）使用大规模并行的内存中操作来识别每个粗粒区段中存在的读物来快速过滤种子位置。我们的评估表明，对于0.05的序列比对误差容限，GRIM过滤器1）将过滤的误报率降低了5.59x–6.41x，并且2）提供了1.81x–3.65的端到端读取映射器加速与采用最先进的先前种子位置过滤算法的最新读取映射器相比，x。 GRIM-Filter利用3D堆栈式内存来实现内存中处理的有效利用，从而克服了种子位置过滤中的内存带宽瓶颈。我们表明，GRIM-Filter显着提高了最新的读取映射器的性能。 GRIM-Filter是一种通用种子位置过滤器，可以应用于任何读取映射器。我们希望我们的结果能为设计其他生物信息学算法的新作品提供灵感，这些算法利用新兴技术和新的处理范例，例如使用3D堆叠存储设备的内存中处理。

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