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Sunday, July 7, 2019

A fast approximate algorithm for mapping long reads to large reference databases.

Emerging single-molecule sequencing technologies from Pacific Biosciences and Oxford Nanopore have revived interest in long-read mapping algorithms. Alignment-based seed-and-extend methods demonstrate good accuracy, but face limited scalability, while faster alignment-free methods typically trade decreased precision for efficiency. In this article, we combine a fast approximate read mapping algorithm based on minimizers with a novel MinHash identity estimation technique to achieve both scalability and precision. In contrast to prior methods, we develop a mathematical framework that defines the types of mapping targets we uncover, establish probabilistic estimates of p-value and sensitivity, and demonstrate tolerance for alignment error rates up to 20%.…

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Sunday, July 7, 2019

Darwin: A genomics co-processor provides up to 15,000 X acceleration on long read assembly

of life in fundamental ways. Genomics data, however, is far outpacing Moore’s Law. Third-generation sequencing tech- nologies produce 100× longer reads than second generation technologies and reveal a much broader mutation spectrum of disease and evolution. However, these technologies incur prohibitively high computational costs. Over 1,300 CPU hours are required for reference-guided assembly of the human genome (using [47]), and over 15,600 CPU hours are required for de novo assembly [57]. This paper describes “Darwin” — a co-processor for genomic sequence alignment that, without sacrificing sensitivity, provides up to 15,000× speedup over the state-of-the-art software for reference-guided assembly of third-generation…

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Sunday, July 7, 2019

BELLA: Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper

De novo assembly is the process of reconstructing genomes from DNA fragments (reads), which may contain redundancy and errors. Longer reads simplify assembly and improve contiguity of the output, but current long-read technologies come with high error rates. A crucial step of de novo genome assembly for long reads consists of finding overlapping reads. We present Berkeley Long-Read to Long-Read Aligner and Overlapper (BELLA), which implement a novel approach to compute overlaps using Sparse Generalized Matrix Multiplication (SpGEMM). We present a probabilistic model which demonstrates the soundness of using short, fixed length k-mers to detect overlaps, avoiding expensive pairwise alignment…

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