Sketching and Sequence Alignment: A Rate-Distortion Perspective
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Pairwise alignment of DNA sequencing data is a ubiquitous task in bioinformatics and typically represents a heavy computational burden. A standard approach to speed up this task is to compute "sketches" of the DNA reads (typically via hashing-based techniques) that allow the efficient computation of pairwise alignment scores. We propose a rate-distortion framework to study the problem of computing sketches that achieve the optimal tradeoff between sketch size and alignment estimation distortion. We consider the simple setting of i.i.d. error-free sources of length n and introduce a new sketching algorithm called "locational hashing." While standard approaches in the literature based on min-hashes require B = (1/D) · O( log n ) bits to achieve a distortion D, our proposed approach only requires B = log^2(1/D) · O(1) bits. This can lead to significant computational savings in pairwise alignment estimation.
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