Rule-based Assembly for Short Read Data Set obtained with Multiple Assemblers and <i>k</i>-mer Sizes

• Item type: SIG Technical Reports(1)
• 公開日: 2015-06-16
• タイトル: Rule-based Assembly for Short Read Data Set obtained with Multiple Assemblers and <i>k</i>-mer Sizes
• タイトル / 言語: en
• タイトル: Rule-based Assembly for Short Read Data Set obtained with Multiple Assemblers and <i>k</i>-mer Sizes
• 言語: eng
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Graduate School of Engineering and Science, University of the Ryukyus
• 著者所属: Graduate School of Medical Research, University of the Ryukyus
• 著者所属: Faculty of Information Engineering, University of the Ryukyus
• 著者所属: Faculty of Information Engineering, University of the Ryukyus
• 著者所属(英): en
• 著者所属(英): Graduate School of Engineering and Science, University of the Ryukyus
• 著者所属(英): en
• 著者所属(英): Graduate School of Medical Research, University of the Ryukyus
• 著者所属(英): en
• 著者所属(英): Faculty of Information Engineering, University of the Ryukyus
• 著者所属(英): en
• 著者所属(英): Faculty of Information Engineering, University of the Ryukyus
• 著者名: Ayako, Oshiro; Hitoshi, Afuso; Takeo, Okazaki; Morikazu, Nakamura
• 著者名(英): Ayako, Oshiro; Hitoshi, Afuso; Takeo, Okazaki; Morikazu, Nakamura
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Various de novo assembly methods based on the idea of k-mer have been proposed. In despite of the success in these methods, another approach, called as Hybrid approach, that combine different traditional methods to take advantages of them have been proposed. However, the results obtained from traditional methods that used in hybrid approach depend on not only the algorithm or heuristics, but also the selection of user-specific k-mer size. Consequently, the results by hybrid approaches also depend on them. In this paper, we designed new assembly approach, called as Rule-based assembly. It follows the strategy similar to the hybrid approach. But it uses certain rules learned from some characteristics of draft contigs to remove erroneous ones and merges them. To construct effective rules, a learning method based on decision tree, called Complex decision tree was proposed. Comparative experiments were also conducted. The results showed that proposed method outperformed traditional one in certain case.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Various de novo assembly methods based on the idea of k-mer have been proposed. In despite of the success in these methods, another approach, called as Hybrid approach, that combine different traditional methods to take advantages of them have been proposed. However, the results obtained from traditional methods that used in hybrid approach depend on not only the algorithm or heuristics, but also the selection of user-specific k-mer size. Consequently, the results by hybrid approaches also depend on them. In this paper, we designed new assembly approach, called as Rule-based assembly. It follows the strategy similar to the hybrid approach. But it uses certain rules learned from some characteristics of draft contigs to remove erroneous ones and merges them. To construct effective rules, a learning method based on decision tree, called Complex decision tree was proposed. Comparative experiments were also conducted. The results showed that proposed method outperformed traditional one in certain case.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA12055912
• 書誌情報: 研究報告バイオ情報学（BIO）; 巻 2015-BIO-42, 号 64, p. 1-8, 発行日 2015-06-16
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 2188-8590
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会