TY - JOUR
T1 - GPU-accelerated and pipelined methylation calling
AU - Feng, Yilin
AU - Gudukbay Akbulut, Gulsum
AU - Tang, Xulong
AU - Gunasekaran, Jashwant Raj
AU - Rahman, Amatur
AU - Medvedev, Paul
AU - Kandemir, Mahmut
N1 - Publisher Copyright:
© 2022 The Author(s). Published by Oxford University Press.
PY - 2022
Y1 - 2022
N2 - Motivation: The third-generation DNA sequencing technologies, such as Nanopore Sequencing, can operate at very high speeds and produce longer reads, which in turn results in a challenge for the computational analysis of such massive data. Nanopolish is a software package for signal-level analysis of Oxford Nanopore sequencing data. Call-methylation module of Nanopolish can detect methylation based on Hidden Markov Model (HMM). However, Nanopolish is limited by the long running time of some serial and computationally expensive processes. Among these, Adaptive Banded Event Alignment (ABEA) is the most time-consuming step, and the prior work, f5c, has already parallelized and optimized ABEA on GPU. As a result, the remaining methylation score calculation part, which uses HMM to identify if a given base is methylated or not, has become the new performance bottleneck. Results: This article focuses on the call-methylation module that resides in the Nanopolish package. We propose Galaxy-methyl, which parallelizes and optimizes the methylation score calculation step on GPU and then pipelines the four steps of the call-methylation module. Galaxy-methyl increases the execution concurrency across CPUs and GPUs as well as hardware resource utilization for both. The experimental results collected indicate that Galaxy-methyl can achieve 3×-5× speedup compared with Nanopolish, and reduce the total execution time by 35% compared with f5c, on average.
AB - Motivation: The third-generation DNA sequencing technologies, such as Nanopore Sequencing, can operate at very high speeds and produce longer reads, which in turn results in a challenge for the computational analysis of such massive data. Nanopolish is a software package for signal-level analysis of Oxford Nanopore sequencing data. Call-methylation module of Nanopolish can detect methylation based on Hidden Markov Model (HMM). However, Nanopolish is limited by the long running time of some serial and computationally expensive processes. Among these, Adaptive Banded Event Alignment (ABEA) is the most time-consuming step, and the prior work, f5c, has already parallelized and optimized ABEA on GPU. As a result, the remaining methylation score calculation part, which uses HMM to identify if a given base is methylated or not, has become the new performance bottleneck. Results: This article focuses on the call-methylation module that resides in the Nanopolish package. We propose Galaxy-methyl, which parallelizes and optimizes the methylation score calculation step on GPU and then pipelines the four steps of the call-methylation module. Galaxy-methyl increases the execution concurrency across CPUs and GPUs as well as hardware resource utilization for both. The experimental results collected indicate that Galaxy-methyl can achieve 3×-5× speedup compared with Nanopolish, and reduce the total execution time by 35% compared with f5c, on average.
UR - http://www.scopus.com/inward/record.url?scp=85153371077&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85153371077&partnerID=8YFLogxK
U2 - 10.1093/bioadv/vbac088
DO - 10.1093/bioadv/vbac088
M3 - Article
C2 - 36699365
AN - SCOPUS:85153371077
SN - 2635-0041
VL - 2
JO - Bioinformatics Advances
JF - Bioinformatics Advances
IS - 1
M1 - vbac088
ER -