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本文引用的文献

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MENDELIAN PROPORTIONS IN A MIXED POPULATION.混合群体中的孟德尔比例
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2
The Mouse Genome Database (MGD): the model organism database for the laboratory mouse.小鼠基因组数据库(MGD):实验小鼠的模式生物数据库。
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3
Linkage analysis in the presence of errors III: marker loci and their map as nuisance parameters.存在误差情况下的连锁分析III:作为干扰参数的标记位点及其图谱
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4
Linkage analysis in the presence of errors IV: joint pseudomarker analysis of linkage and/or linkage disequilibrium on a mixture of pedigrees and singletons when the mode of inheritance cannot be accurately specified.存在错误情况下的连锁分析IV:当遗传模式无法准确确定时,对家系和单病例混合样本进行连锁和/或连锁不平衡的联合伪标记分析
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5
Linkage analysis in the presence of errors II: marker-locus genotyping errors modeled with hypercomplex recombination fractions.存在错误情况下的连锁分析II:用超复数重组分数对标记-基因座基因分型错误进行建模
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Linkage analysis in the presence of errors I: complex-valued recombination fractions and complex phenotypes.存在错误情况下的连锁分析I:复数值重组率和复杂表型
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Incorrect specification of marker allele frequencies: effects on linkage analysis.标记等位基因频率的错误设定:对连锁分析的影响。
Am J Hum Genet. 1993 Jun;52(6):1102-10.

在分子实验室中检测高通量基因型数据错误的简单测试。

Simple tests to detect errors in high-throughput genotype data in the molecular laboratory.

作者信息

Vandenbergh David J, Heron Kathrine, Peterson Ryan, Shpargel Karl B, Woodroffe Abigail, Blizard David A, McClearn Gerald E, Vogler George P

机构信息

Center for Developmental and Health Genetics, Department of Biobehavioral Health, and Life Sciences Consortium, The Pennsylvania State University, University Park, PA 16802, USA.

出版信息

J Biomol Tech. 2003 Mar;14(1):9-16.

PMID:12901607
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2279894/
Abstract

With the advent of high-density DNA marker data sets for the mouse and other model systems, 100 or more genotype are routinely generated from large groups of mice. Issues of the accuracy and reliability of the genotyping are extremely important but often not addressed until genetic analysis is conducted. Simple tests that rely on the robust predictions arising from Mendelian genetics can be made quickly in the molecular laboratory as the data are generated, and require only a spreadsheet program. In this report, genotype data from 392 mice tested at 96 marker sites were analyzed for errors that are typical when handling large volumes of data generated in a repetitive process. The testing consisted of: (1) repeating the genotyping of approximately 1% of the samples; (2) examining the deviation from the expected segregation ratio ( 1:2:1 ) on a marker-by-marker basis; and (3) testing the correlation of the genotype at one marker with that at neighboring genetic markers on a chromosome. These three steps allowed analysis at the level of the microtiter plate, where errors are most likely to occur. A set of 96 dinucleotide repeat markers that are polymorphic between the C57BL/6J and DBA/2J mouse strains and can be multiplexed is reported for use in other genotyping projects.

摘要

随着小鼠和其他模型系统的高密度DNA标记数据集的出现,通常可以从大量小鼠中生成100个或更多的基因型。基因分型的准确性和可靠性问题极其重要,但在进行遗传分析之前往往未得到解决。在分子实验室生成数据时,可以根据孟德尔遗传学的可靠预测快速进行简单测试,并且只需要一个电子表格程序。在本报告中,分析了在96个标记位点测试的392只小鼠的基因型数据,以查找在处理重复过程中生成的大量数据时常见的错误。测试包括:(1)对约1%的样本重复进行基因分型;(2)逐个标记地检查与预期分离比(1:2:1)的偏差;(3)测试一个标记处的基因型与染色体上相邻遗传标记处的基因型的相关性。这三个步骤允许在微量滴定板水平进行分析,因为此处最容易出现错误。本文报道了一组96个二核苷酸重复标记,它们在C57BL/6J和DBA/2J小鼠品系之间具有多态性并且可以进行多重分析,可用于其他基因分型项目。