近隣剪定法: 進化系統樹を利用した配列リサンプリングアルゴリズム

摘要

Recently alarge number of nucleotide sequences of various pathogens are available in public databases. The growth of the datasets has resulted in an enormous increase in computational costs. Moreover, due to differences in surveillance activities, the number of sequences found in databases varies from one country to another and from year to year. Therefore it is important to study resampling methods to reduce the sampling oias. In this paper we propose a novel algorithm-called the closest-neighbor trimming method-that resamples a given number of sequences from alarge nucleotide sequence dataset. We compare the performance of the proposed algorithm with other algorithms by using the nucleotide sequences of human H3N2 influenza viruses.%近年,インフルエンザをはじめ様々な病原体の遗伝子情報が大量に蓄積されつつある.データセッ卜の増大に伴い,配列解析にかかる計算コストが急増している.また,疫学調査活動の差異により,データセットは調査地域や年代に関して大きなサンプリングバイアスを含む.本研究では,進化系統榭を利用してサンプリング密度の高い配列を適宜取り除くリサンプリングアルゴリズムを提案し,その性能を比較実験により評価する.