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    題名: TCS: A New Multiple Sequence Alignment Reliability Measure to Estimate Alignment Accuracy and Improve Phylogenetic Tree Reconstruction
    作者: 張家銘
    Chang, Jia-Ming;Tommaso, Paolo Di;Notredame, Cedric
    貢獻者: 資科系
    關鍵詞: T-Coffee;multiple sequence alignment;alignment uncertainty;alignment confidence;phylogeny;homology modeling
    日期: 2014-06
    上傳時間: 2016-05-30 17:24:17 (UTC+8)
    摘要: Multiple sequence alignment (MSA) is a key modeling procedure when analyzing biological sequences. Homology and evolutionary modeling are the most common applications of MSAs. Both are known to be sensitive to the underlying MSA accuracy. In this work, we show how this problem can be partly overcome using the transitive consistency score (TCS), an extended version of the T-Coffee scoring scheme. Using this local evaluation function, we show that one can identify the most reliable portions of an MSA, as judged from BAliBASE and PREFAB structure-based reference alignments. We also show how this measure can be used to improve phylogenetic tree reconstruction using both an established simulated data set and a novel empirical yeast data set. For this purpose, we describe a novel lossless alternative to site filtering that involves overweighting the trustworthy columns. Our approach relies on the T-Coffee framework; it uses libraries of pairwise alignments to evaluate any third party MSA. Pairwise projections can be produced using fast or slow methods, thus allowing a trade-off between speed and accuracy. We compared TCS with Heads-or-Tails, GUIDANCE, Gblocks, and trimAl and found it to lead to significantly better estimates of structural accuracy and more accurate phylogenetic trees. The software is available from www.tcoffee.org/Projects/tcs.
    關聯: Molecular Biology and Evolution, Vol.31, No.6, pp.1625-37
    資料類型: article
    DOI 連結: http://dx.doi.org/10.1093/molbev/msu117
    DOI: 10.1093/molbev/msu117
    顯示於類別:[資訊科學系] 期刊論文

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