bioRxivBioinformaticsPreprint
Acceleration Of Nucleotide Semi-Global Alignment With Adaptive Banded Dynamic Programming
Abstract
MotivationPairwise alignment of nucleotide sequences has previously been carried out using the seed- and-extend strategy, where we enumerate seeds (shared patterns) between sequences and then extend the seeds by Smith-Waterman-like semi-global dynamic programming to obtain full pairwise alignments. With the advent of massively parallel short read sequencers, algorithms and data structures for efficiently finding seeds have been extensively explored. However, recent advances in single-molecule sequencing technologies have enabled us to obtain millions of reads, each of which is orders of magnitude longer than those output by the short-read sequencers, demanding a faster algorithm for the extension step that accounts for most of the computation time required for pairwise local alignment. Our goal is to design a faster extension algorithm suitable for single-molecule sequencers with high sequencing error rates (e.g., 10-15%) and with more frequent insertions and deletions than substitutions.\n\nResultsWe propose an adaptive banded dynamic programming algorithm for calculating pairwise semi-global alignment of nucleotide sequences that allows a relatively high insertion or deletion rate while keeping band width relatively low (e.g., 32 or 64 cells) regardless of sequence lengths. Our new algorithm eliminated mutual dependences between elements in a vector, allowing an efficient Single-Instruction-Multiple-Data parallelization. We experimentally demonstrate that our algorithm runs approximately 5x faster than the extension alignment algorithm in NCBI BLAST+ while retaining similar sensitivity (recall).\n\nWe also show that our extension algorithm is more sensitive than the extension alignment routine in DALIGNER, while the computation time is comparable.\n\nAvailabilityThe implementation of the algorithm and the benchmarking scripts are available at https://github.com/ocxtal/adaptivebandbench.\n\nContactmkasa@edu.k.u-tokyo.ac.jp
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: sequence-to-function modeling
- research focus: benchmarking
- approach: statistical model
- approach: matrix factorization
- Citations
- 31
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- BSAlign: a library for nucleotide sequence alignment
Haojing Shao, Jue Ruan·Genomics Proteomics & BioinformaticsPeer-reviewed·Mar 14, 2024
- Block aligner: fast and flexible pairwise sequence alignment with SIMD-accelerated adaptive blocks
Daniel Liu, Martin Steinegger·bioRxiv·Nov 8, 2021
- QuickEd: High-performance exact sequence alignment based on bound-and-align
Max Doblas, Oscar Lostes-Cazorla, … Santiago Marco‐Sola·BioinformaticsPeer-reviewed·Mar 1, 2025
- Exact global alignment using A* with chaining seed heuristic and match pruning
Ragnar Groot Koerkamp, Pesho Ivanov·BioinformaticsPeer-reviewed·Jan 20, 2024
- Flexible seed size enables ultra-fast and accurate read alignment
Kristoffer Sahlin·Genome biologyPeer-reviewed·Dec 15, 2022
- TSTA: Thread and SIMD-Based Trapezoidal Pairwise/Multiple Sequence Alignment Method
Peiyu Zong, Wenpeng Deng, … Jue Ruan·GigabytePeer-reviewed·Nov 5, 2024