東京大学医科学研究所

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学友会セミナー

学友会セミナー:2019年12月20日

開催日時: 2019年12月20日 13:00 ~ 16:00
開催場所: 2号館 大講義室
講師: Mohammed H. K. Alser
所属: Lecturer and Senior Researcher, Department of Computer Science, ETH Zurich
演題: A Roadmap for Fast and Efficient Genome Analysis
概要:

Our understanding of human genomes today is affected by the ability of modern computing technology to quickly and accurately determine an individual’s entire genome. Over the past decade, high throughput sequencing (HTS) technologies have opened the door to remarkable biomedical discoveries through its ability to generate hundreds of millions to billions of DNA segments per run along with a substantial reduction in time and cost. To analyze a genome, each of these segments -called reads- must be mapped to a reference genome based on the similarity between a read and “candidate” locations in that reference genome. This process is called read mapping and it is currently a major bottleneck in the entire genome analysis pipeline as the flood of sequencing data continues to overwhelm the processing capacity of existing algorithms and hardware. It gets even worse when one tries to understand a complex disease (e.g., autism and cancer) or profile a metagenomics sample, which requires analyzing hundreds of thousands of genomes. The long execution time of modern-day sequence aligners can severely hinder such studies. There is also an urgent need for rapidly incorporating clinical DNA sequencing and analysis into clinical practice for early diagnosis of genetic disorders in critically ill infants and saving their life. This makes the development of fundamentally new, fast, and efficient read mapper the utmost necessity.

This talk describes our ongoing journey in significantly improving the performance of genome read mapping. We first provide a brief background on read mappers that can comprehensively find variations in genomes and tolerate sequencing errors. Then, we describe our new algorithmic methods and hardware-based acceleration approaches. Algorithmic approaches exploit the structure of the genome as well as the structure of the underlying hardware. Hardware-based acceleration approaches exploit specialized microarchitectures or new execution paradigms, like processing in memory. We show that significant improvements are possible with algorithmic methods, hardware accelerators, and their combination. We conclude with a foreshadowing of future challenges and research directions triggered by the development of very low cost yet highly error prone new sequencing technologies.

世話人: 〇渋谷 哲朗 (シークエンスデータ情報処理分野)
 井元 清哉 (健康医療データサイエンス分野)