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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 30-May-2016 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 http://dx.doi.org/10.1093/molbev/msu117
dc.contributor 資科系
dc.creator (作者) 張家銘zh_TW
dc.creator (作者) Chang, Jia-Ming;Tommaso, Paolo Di;Notredame, Cedric
dc.date (日期) 2014-06
dc.date.accessioned 30-May-2016 17:24:17 (UTC+8)-
dc.date.available 30-May-2016 17:24:17 (UTC+8)-
dc.date.issued (上傳時間) 30-May-2016 17:24:17 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/97013-
dc.description.abstract (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.
dc.format.extent 602817 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Molecular Biology and Evolution, Vol.31, No.6, pp.1625-37
dc.subject (關鍵詞) T-Coffee ; multiple sequence alignment ; alignment uncertainty ; alignment confidence ; phylogeny ; homology modeling
dc.title (題名) TCS: A New Multiple Sequence Alignment Reliability Measure to Estimate Alignment Accuracy and Improve Phylogenetic Tree Reconstruction
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1093/molbev/msu117
dc.doi.uri (DOI) http://dx.doi.org/10.1093/molbev/msu117