ADaM: Augmenting Existing Approximate Fast Matching Algorithms with Efficient and Exact Range Queries

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Clement, Nathan L.
Thompson, Lee P.
Miranker, Daniel P.

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Drug discovery, disease detection, and personalized medicine are fast-growing areas of genomic research. With the advancement of next-generation sequencing techniques, researchers can obtain an abundance of data for many different biological assays in a short period of time. When this data is error-free, the result is a high-quality base-pair resolution picture of the genome. However, when the data is lossy the heuristic algorithms currently used when aligning next-generation sequences causes the corresponding accuracy to drop. Results: This paper describes a program, ADaM (APF DNA Mapper) which significantly increases final alignment accuracy. ADaM works by first using an existing program to align "easy" sequences, and then using an algorithm with accuracy guarantees (the APF) to align the remaining sequences. The final result is a technique that increases the mapping accuracy from only 60% to over 90% for harder-to-align sequences.


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Clement, Nathan L., Lee P. Thompson, and Daniel P. Miranker. "ADaM: augmenting existing approximate fast matching algorithms with efficient and exact range queries." BMC bioinformatics, Vol. 15, No. Suppl 7 (May, 2014): S1.