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

Autor: Kim JS; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA. jeremiekim123@gmail.com.; Department of Computer Science, ETH Zürich, Zürich, CH, Switzerland. jeremiekim123@gmail.com., Senol Cali D; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA., Xin H; Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA., Lee D; NVIDIA Research, Austin, TX, USA., Ghose S; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA., Alser M; Department of Computer Engineering, Bilkent University, Bilkent, Ankara, Turkey., Hassan H; Department of Computer Science, ETH Zürich, Zürich, CH, Switzerland., Ergin O; Department of Computer Engineering, TOBB University of Economics and Technology, Sogutozu, Ankara, Turkey., Alkan C; Department of Computer Engineering, Bilkent University, Bilkent, Ankara, Turkey., Mutlu O; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA. omutlu@gmail.com.; Department of Computer Science, ETH Zürich, Zürich, CH, Switzerland. omutlu@gmail.com.
Jazyk: angličtina
Zdroj: BMC genomics [BMC Genomics] 2018 May 09; Vol. 19 (Suppl 2), pp. 89. Date of Electronic Publication: 2018 May 09.
DOI: 10.1186/s12864-018-4460-0
Abstrakt: 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 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.
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.
Databáze: MEDLINE
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