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GRIM-Filter: Fast seed location filtering in DNA read mapping using processing-in-memory technologies

机译:Grim-Filter:使用加工内存技术读取DNA读取映射的快速种子位置滤波

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Background: 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.Results: 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 showthat 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 thebest previous seed location filtering algorithm.Conclusion: 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:背景:种子定位滤波在DNA读取映射中是至关重要的,其中从供体中取样的数十亿个DNA片段(读数)的过程被映射到参考基因组上以鉴定供体的基因组变体。最先进的读取映射器1)在每个读取位置的每个读取位置和3)中快速生成每个读取的种子(即,较小段)的种子(即,较小段)的可能映射位置,以及3)检查每个读取之间的相似性具有计算上昂贵的算法(即,序列对准)的相关参考序列以确定读取的来源。在对齐之前,种子定位过滤器在发挥作用中,丢弃了对准的种子位置将认为差距不佳。理想的种子定位过滤器将在对齐之前丢弃所有差的匹配位置,使得在不必要的对齐上没有浪费的计算。结果:我们提出了一种新颖的种子定位滤波算法,Grim-滤波器,优化,以利用集成的3D堆叠的内存系统在存储器层下堆叠的逻辑层内的计算,以执行内存处理(PIM)。更加严峻过滤器快速过滤1)通过大规模并行内存操作来介绍参考基因组的粗粒度段的新表示,并在每个粗粒段内识别读出。我们的评估显示为0.05的序列对准误差容错,Grim-滤波器1)降低了滤波的假负速率5.59x-6.41x,2)提供了1.81x-3.65x的端到端读取映射器加速相比,与现有技术的readper相比,采用最先前种子定位过滤算法的映射器。结论:Grim-Filter利用3D堆叠内存,这使得能够有效地使用处理内存,克服内存带宽瓶颈在种子定位过滤中。我们表明,Grim-滤波器显着提高了最先进的映射器的性能。 Grim-Filter是一个通用种子定位滤波器,可应用于任何读取的映射器。我们希望我们的结果为新作品提供灵感来设计其他生物信息学算法,这些算法利用新兴技术和新的处理范例,例如使用3D堆叠存储器设备的加工内存。

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