GaKCo: a Fast Gappedk-mer string Kernel using Counting Article Swipe

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Ritambhara Singh , Arshdeep Sekhon , Jack Lanchantin , Kamran Kowsari , Beilun Wang , Yanjun Qi ·

YOU? · · 2018 · Open Access · · DOI: https://doi.org/10.1101/329425

String Kernel (SK) techniques, especially those using gapped k -mers as features (gk), have obtained great success in classifying sequences like DNA, protein, and text. However, the state-of-the-art gk-SK runs extremely slow when we increase the dictionary size ( Σ ) or allow more mismatches ( M ). This is because current gk-SK uses a trie-based algorithm to calculate co-occurrence of mismatched substrings resulting in a time cost proportional to O ( Σ M ). We propose a fast algorithm for calculating Ga pped k -mer K ernel using Co unting (GaKCo). GaKCo uses associative arrays to calculate the co-occurrence of substrings using cumulative counting. This algorithm is fast, scalable to larger Σ and M , and naturally parallelizable. We provide a rigorous asymptotic analysis that compares GaKCo with the state-of-the-art gk-SK. Theoretically, the time cost of GaKCo is independent of the Σ M term that slows down the trie-based approach. Experimentally, we observe that GaKCo achieves the same accuracy as the state-of-the-art and outperforms its speed by factors of 2, 100, and 4, on classifying sequences of DNA (5 datasets), protein (12 datasets), and character-based English text (2 datasets). 1

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Substring Trie Kernel (algebra) String (physics) Computer science k-mer Scalability Parallelizable manifold Algorithm State (computer science) Character (mathematics) Mathematics Combinatorics Data structure DNA DNA sequencing Geometry Database Biology Programming language Genetics Mathematical physics

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Type: preprint
Language: en
Landing Page: https://doi.org/10.1101/329425
PDF: https://www.biorxiv.org/content/biorxiv/early/2018/05/24/329425.full.pdf
OA Status: green
Cited By: 4
References: 33
Related Works: 10
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DOI: https://doi.org/10.1101/329425

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Title: GaKCo: a Fast Gappedk-mer string Kernel using Counting

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Type: preprint

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Language: en

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Publication year: 2018

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Publication date: 2018-05-24

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Authors: Ritambhara Singh, Arshdeep Sekhon, Jack Lanchantin, Kamran Kowsari, Beilun Wang, Yanjun Qi

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Landing page: https://doi.org/10.1101/329425

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Concepts: Substring, Trie, Kernel (algebra), String (physics), Computer science, k-mer, Scalability, Parallelizable manifold, Algorithm, State (computer science), Character (mathematics), Mathematics, Combinatorics, Data structure, DNA, DNA sequencing, Geometry, Database, Biology, Programming language, Genetics, Mathematical physics

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Cited by: 4

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Citations by year (recent): 2023: 1, 2020: 2, 2019: 1

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References (count): 33

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Related works (count): 10

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