var_test_gwaa(VariABEL)
var_test_gwaa()所属R语言包：VariABEL
Function performs compariosn of genotypic variances.
功能执行基因型差异的compariosn的。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Presence of significant difference of genotypic variances points to possible Significant variance difference points to possible presence of interaction between a tested SNP and a factor (or set of factors).
存在显着差异的基因型差异点可能显着差异差异点，可能存在一个经过测试的SNP和一个系数（或因素）之间的互动。
用法----------Usage----------
var_test_gwaa(formula, genodata, phenodata, genodata_info=NULL, testname="svlm", analysis_type="AAvsABvsBB")
参数----------Arguments----------
参数：formula
Regression model used for analysis. In the first stage linear regression is run to exclude main snp effect. In this stage adjustment for covariates is performed.
回归模型进行分析。在第一阶段中，线性回归运行排除主SNP效果。在这个阶段的协变量进行调整。
参数：genodata
The genotypes data in format of genabel or databel object.
基因型数据格式genabel或databel对象。
参数：phenodata
The phenotypes data in format of data.frame object.
表型数据格式的数据框对象。
参数：genodata_info
The file with snp information (name, position). Used if genodata is databel object.
SNP信息（姓名，职务）的文件。用于，如果genodata databel对象。
参数：testname
Name of variance heterogeneity test to perform. svlm (for imputed genotype data), levene, and bartlett test are supported.
异方差检验的名称来执行。 svlm（估算基因型数据），列文爵士，和Bartlett检验的支持。
参数：analysis_type
Type of analsysis to perform. AAvsABvsBB - additive model where B allele additivly increase risk, AAvsABandBB - group AA tested agains AB and BB, ABvsAAandBB - AB against AA and BB, BBvsAAandAB - BB against AA and AB. Only available for typed snps.
类型的analsysis执行。 AAvsABvsBB - 添加剂模型，其中B的等位基因additivly增加的风险，AAvsABandBB - AA组测试，ABvsAAandBB agains AB和BB - AB对AA和BB，BBvsAAandAB - BB对AA型和AB型。仅适用于类型的SNP位点。
Details
详细信息----------Details----------
The function var_test_gwaa tests for difference in genotypic variances. This difference points to presence of possible interaction between the tested SNP and some factor. In the case svlm test the analysis consists of two stage: firstly the regular GWA id done where regression analysis is performed with covariates specified in the input parameter formula, in the second stage the regression analysis is performed with using residuals from the first stage and a sno as a covariate.
该的功能var_test_gwaa测试差异的基因型差异。这种差异指向被测SNP和某些因子之间的可能的相互作用的存在。在的情况下svlm测试分析包括两个阶段：首先经常GWA的id做进行回归分析的输入参数中公式指定的协变量，在第二阶段中进行回归分析是使用来自第一级和一个残差SNO作为协变量。
值----------Value----------
The ouput is a data.frame object. The table contains the chisq of variance heterogeneity test (the name is chisq) the effects and standart errors of all covariates included into regression model, main snp effect (the names are snp_eff and snp_se). In the case of svlm test the columns snp_eff_dispertion and snp_se_dispertion contain effect of a snp on squared vallues of a trait.
将输出数据框对象。该表包含chisq的异方差检验（名称是chisq的）的所有协变量纳入回归模型，主要SNP效果（的的名字是snp_eff和snp_se）的影响和非标准的错误。在箱子svlm测试列snp_eff_dispertion和snp_se_dispertion包含上的性状的vallues平方效果的SNP。
（作者）----------Author(s)----------
Maksim Struchalin
参考文献----------References----------
interacting genetic loci: method and its limitations. BMC Genetics 2010, 11:92, doi:10.1186/1471-2156-11-92
potentially interacting loci by testing genotypic variance heterogeneity. Submitted.
实例----------Examples----------
if (require(GenABEL))
{
data(srdta)
result1 <- var_test_gwaa(bt~qt1+qt2, genodata=gtdata(srdta), phenodata=phdata(srdta))
#if there is no covariates needed:[如果有没有协变量需要：]
result2 <- var_test_gwaa("bt", genodata=gtdata(srdta), phenodata=phdata(srdta))
}
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-1 14:24:45
