GPU accelerated adaptive banded event alignment for rapid comparative nanopore signal analysis.

ABSTRACT:

Background

Nanopore sequencing enables portable, real-time sequencing applications, including point-of-care diagnostics and in-the-field genotyping. Achieving these outcomes requires efficient bioinformatic algorithms for the analysis of raw nanopore signal data. However, comparing raw nanopore signals to a biological reference sequence is a computationally complex task. The dynamic programming algorithm called Adaptive Banded Event Alignment (ABEA) is a crucial step in polishing sequencing data and identifying non-standard nucleotides, such as measuring DNA methylation. Here, we parallelise and optimise an implementation of the ABEA algorithm (termed f5c) to efficiently run on heterogeneous CPU-GPU architectures.

Results

By optimising memory, computations and load balancing

SUBMITTER: Gamaarachchi H 

PROVIDER: S-EPMC7430849 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature