In silico analysis of missense substitutions using sequence-alignment based methods.
In silico analysis of missense substitutions using sequence-alignment based methods.
复制标题
DOI：
10.1002/humu.20892
复制
发表时间：
2008-11
期刊：
影响因子：
3.9
通讯作者：
Byrnes, Graham B.
中科院分区：
文献类型：
--
作者：
Tavtigian, Sean V.;Greenblatt, Marc S.;Lesueur, Fabienne;Byrnes, Graham B.
对高危癌症易感基因突变的基因测试经常会发现错义替换，这些错义替换不容易被归类为致病或中性。可以帮助对它们进行分类的方法包括计算分析。对致病与中性的预测，或变异体致病的可能性，可以基于1)对几乎任何错义序列变体使用感兴趣基因的蛋白质多序列比对(PMSA)从进化保守中推断，以及2)对于许多变异体，野生型和变异型蛋白质的结构特征。这些在硅胶方法中的应用在最近几年有了很大的改进。在本文中，我们回顾和/或就以下方面提出建议：1)在计算机方法中使用以帮助预测错义变量后果的基本原理，2)创建用于分类的信息的PMSA的重要方面，3)已经用于临床观察的变量分类的算法的特定特征，4)验证研究证明计算分析可以具有~75-95%的预测值，5)为了改进计算分类器而需要解决的数据集和算法的当前限制，以及6)计算机算法如何可以成为多行证据的“综合分析”的一部分以帮助分类变量。我们的结论是，在其他证据的背景下，仔细验证的计算算法可以成为分类错义变体的重要工具。
Genetic testing for mutations in high-risk cancer susceptibility genes often reveals missense substitutions that are not easily classified as pathogenic or neutral. Among the methods that can help in their classification are computational analyses. Predictions of pathogenic vs neutral, or the probability that a variant is pathogenic, can be made based on 1) inferences from evolutionary conservation using protein multiple sequence alignments (PMSAs) of the gene of interest for almost any missense sequence variant, and 2) for many variants, structural features of wild type and variant proteins. These in silico methods have improved considerably in recent years. In this paper, we review and/or make suggestions with respect to 1) the rationale for using in silico methods to help predict the consequences of missense variants, 2) important aspects of creating PMSAs that are informative for classification, 3) specific features of algorithms that have been used for classification of clinically observed variants, 4) validation studies demonstrating that computational analyses can have predictive values of ~75–95%, 5) current limitations of data sets and algorithms that need to be addressed in order to improve the computational classifiers, and 6) how in silico algorithms can be a part of the “integrated analysis” of multiple lines of evidence to help classify variants. We conclude that carefully validated computational algorithms, in the context of other evidence, can be an important tool for classification of missense variants.
登录
查看更多内容
DOI：
10.1073/pnas.89.22.10915
发表时间：
1992-11-15
影响因子：
11.1
作者：
HENIKOFF, S;HENIKOFF, JG
通讯作者：
HENIKOFF, JG
影响因子：
9.8
作者：
Easton, Douglas F.;Deffenbaugh, Amie M.;Goldgar, David E.
通讯作者：
Goldgar, David E.
影响因子：
5.8
作者：
Care, Matthew A.;Needham, Chris J.;Westhead, David R.
通讯作者：
Westhead, David R.
影响因子：
11.2
作者：
Judkins, T;Hendrickson, BC;Scholl, T
通讯作者：
Scholl, T
DOI：
10.1089/10906570260199375
发表时间：
2002-06-01
期刊：
GENETIC TESTING
影响因子：
--
作者：
Deffenbaugh, AM;Frank, TS;Neuhausen, SL
通讯作者：
Neuhausen, SL