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EvalMSA:一个用于评估多序列比对并检测异常值的程序。

EvalMSA: A Program to Evaluate Multiple Sequence Alignments and Detect Outliers.

作者信息

Chiner-Oms Alvaro, González-Candelas Fernando

机构信息

Joint Research Unit "Infection and Public Health" FISABIO, Cavanilles Institute for Biodiversity and Evolutionary Biology, University of Valencia, Paterna, Valencia, Spain.; CIBER in Epidemiology and Public Health, Madrid, Spain.

出版信息

Evol Bioinform Online. 2016 Nov 28;12:277-284. doi: 10.4137/EBO.S40583. eCollection 2016.

DOI:10.4137/EBO.S40583
PMID:27920488
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5127606/
Abstract

We present EvalMSA, a software tool for evaluating and detecting outliers in multiple sequence alignments (MSAs). This tool allows the identification of divergent sequences in MSAs by scoring the contribution of each row in the alignment to its quality using a sum-of-pair-based method and additional analyses. Our main goal is to provide users with objective data in order to take informed decisions about the relevance and/or pertinence of including/retaining a particular sequence in an MSA. EvalMSA is written in standard Perl and also uses some routines from the statistical language R. Therefore, it is necessary to install the R-base package in order to get full functionality. Binary packages are freely available from http://sourceforge.net/projects/evalmsa/for Linux and Windows.

摘要

我们展示了EvalMSA,这是一种用于评估和检测多序列比对(MSA)中异常值的软件工具。该工具通过使用基于成对求和的方法及其他分析,对比对中每行对其质量的贡献进行评分,从而识别MSA中的差异序列。我们的主要目标是为用户提供客观数据,以便就将特定序列纳入/保留在MSA中的相关性和/或适用性做出明智决策。EvalMSA是用标准Perl编写的,还使用了统计语言R中的一些例程。因此,有必要安装R-base包以获得完整功能。二进制包可从http://sourceforge.net/projects/evalmsa/免费获取,适用于Linux和Windows。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcd/5127606/bd07185cca54/ebo-12-2016-277f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcd/5127606/6e4f836bc53a/ebo-12-2016-277f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcd/5127606/fa0005568f57/ebo-12-2016-277f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcd/5127606/bd07185cca54/ebo-12-2016-277f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcd/5127606/6e4f836bc53a/ebo-12-2016-277f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcd/5127606/fa0005568f57/ebo-12-2016-277f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcd/5127606/bd07185cca54/ebo-12-2016-277f3.jpg

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