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Short-Read DNA Sequence Alignment with Custom Designed FPGA-based Hardware

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Short-read shotgun DNA sequencing is the determination of the sequence of a large number of DNA reads which have been chemically cut out of the genome sequence of a particular individual. Short-read DNA Sequencing is the underlying lab method which will be used for “personal genomics.” Personal genomics is the tailoring of medical treatments for a particular individual. One area where personal genomics is likely to have a big impact is cancer treatment. It’s likely to provide a more accurate and automated method to map anti-cancer chemotherapy drugs to particular cases of cancer than current methods. To tailor a treatment to a particular individual requires identifying the important differences between the standard human genome sequence and the genome sequence of that particular individual. Of the methods used for doing this, it appears that aligning the short reads to the standard reference genome is a necessary pre-processing step.

The rate at which short read DNA sequence data is being produced doubles every 5 months due to improvements in the hardware of the laboratory equipment. As a result, performing this alignment in a computationally efficient way is becoming increasingly important. We demonstrate how we can exploit the ``embarrassingly parallel’’ property of short read sequence alignment in custom-designed hardware in FPGA ’s. Hardware is chosen, a system is designed, and this system is implemented. My FPGA -based hit finder was demonstrated to produce correct hit results. The performance of this single FPGA implementation was demonstrated to be 71,000 seed hits found per hour on a human genome sized reference sequence. The implementation was demonstrated to produce identical results to the hit finder stage of the widely-used software aligner MAQ . We demonstrate that the price/performance of this sliding-window FPGA aligner (approximately 355 seeds/hr/$) compares favorably to the price/performance of sliding-window software aligners (approximately 67.5 seeds/hr/$ for MAQ ). However, software aligners which are based on the superior Burrows-Wheeler alignment algorithm still have a significant price/performance advantage over the FPGA -based approach (approximately 7,200 seeds/hr/$). We predict that as chips continue to increase in size due to Moore’s Law and computation is performed in high-density cloud-computing datacenters the FPGA -based approach will become preferable to current software aligners.

This talk is part of the Computer Laboratory Computer Architecture Group Meeting series.

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