bioRxivBioinformaticsPreprint
AStarix: Fast and Optimal Sequence-to-Graph Alignment
Pesho IvanoviD, Benjamin BichseliD, Harun MustafaiD, André KahlesiD, Gunnar RätschiD, Martin VecheviD
- Citations
- 5
Abstract
We present an algorithm for the optimal alignment of sequences to genome graphs. It works by phrasing the edit distance minimization task as finding a shortest path on an implicit alignment graph. To find a shortest path, we instantiate the A[*] paradigm with a novel domain-specific heuristic function that accounts for the upcoming subsequence in the query to be aligned, resulting in a provably optimal alignment algorithm called ASO_SCPLOWTARIXC_SCPLOW. Experimental evaluation of ASO_SCPLOWTARIXC_SCPLOW shows that it is 1-2 orders of magnitude faster than state-of-the-art optimal algorithms on the task of aligning Illumina reads to reference genome graphs. Implementations and evaluations are available at https://github.com/eth-sri/astarix.
- assay: whole-genome sequencing
- research focus: sequence-to-function modeling
- research focus: benchmarking
- approach: statistical model
- approach: optimal transport
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