GateKeeper-GPU: accelerated pre-alignment filtering in short read mapping
Embargo Lift Date: 2021-03-03
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Recent advances in high throughput sequencing (HTS) facilitate fast production of short DNA fragments (reads) in numerous amounts. Although the production is becoming inexpensive everyday, processing the present data for sequence alignment as a whole procedure is still computationally expensive. As the last step of alignment, the candidate locations of short reads on the reference genome are veriﬁed in accordance with their diﬀerence from the corresponding reference segment with the least possible error. In this sense, comparison of reads and reference segments requires approximate string matching techniques which traditionally inherit dynamic programming algorithms. Performing dynamic programming for each of the read and reference segment pair makes alignment, a computationally-costly stage for mapping process. So, accelerating this stage is expected to improve alignment performance in terms execution time. Here, we propose, GateKeeper-GPU, a fast pre-alignment ﬁlter to be performed before veriﬁcation to get rid of the sequence pairs, which exceed a predeﬁned error threshold, for reducing the computational load on the dynamic programming. We choose GateKeeper as the ﬁltration algorithm, we improve and implement it on a GPGPU platform with CUDA framework to obtain beneﬁt from performing compute-intensive work with highly parallel and independent millions of threads for boosting performance. GateKeeper-GPU can accelerate veriﬁcation stage by up to 2.9× and provide up to 1.4× speedup for overall read alignment procedure when integrated with mrFAST, while producing up to 52× less number of false accept pairs than original GateKeeper work.
General purpose graphical processing unit (GPGPU)