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On the Complexity of Sequence to Graph Alignment

Chirag Jain, Haowen Zhang, Yu Gao, Srinivas Aluru
doi: https://doi.org/10.1101/522912
Chirag Jain
College of Computing, Georgia Institute of Technology
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Haowen Zhang
College of Computing, Georgia Institute of Technology
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Yu Gao
College of Computing, Georgia Institute of Technology
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Srinivas Aluru
College of Computing, Georgia Institute of Technology
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Abstract

Availability of extensive genetics data across multiple individuals and populations is driving the growing importance of graph based reference representations. Aligning sequences to graphs is a fundamental operation on several types of sequence graphs (variation graphs, assembly graphs, pan-genomes, etc.) and their biological applications. Though research on sequence to graph alignments is nascent, it can draw from related work on pattern matching in hypertext. In this paper, we study sequence to graph alignment problems under Hamming and edit distance models, and linear and affine gap penalty functions, for multiple variants of the problem that allow changes in query alone, graph alone, or in both. We prove that when changes are permitted in graphs either standalone or in conjunction with changes in the query, the sequence to graph alignment problem is Embedded Image-complete under both Hamming and edit distance models for alphabets of size ≥ 2. For the case where only changes to the sequence are permitted, we present an O(|V| + m|E|) time algorithm, where m denotes the query size, and V and E denote the vertex and edge sets of the graph, respectively. Our result is generalizable to both linear and affine gap penalty functions, and improves upon the run-time complexity of existing algorithms.

Footnotes

  • aluru{at}cc.gatech.edu

  • ↵* Should be regarded as joint first-authors.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted January 17, 2019.
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On the Complexity of Sequence to Graph Alignment
Chirag Jain, Haowen Zhang, Yu Gao, Srinivas Aluru
bioRxiv 522912; doi: https://doi.org/10.1101/522912
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On the Complexity of Sequence to Graph Alignment
Chirag Jain, Haowen Zhang, Yu Gao, Srinivas Aluru
bioRxiv 522912; doi: https://doi.org/10.1101/522912

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