snp.lhs.tests(chopsticks)
snp.lhs.tests()所属R语言包：chopsticks
Score tests with SNP genotypes as dependent variable
作为因变量分数与SNP基因型测试
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Under the assumption of Hardy-Weinberg equilibrium, a SNP genotype is a binomial variate with two trials for an autosomal SNP or with one or two trials (depending on sex) for a SNP on the X chromosome. With each SNP in an input "snp.matrix" as dependent variable, this function first fits a "base" logistic regression model and then carries out a score test for the addition of further term(s). The Hardy-Weinberg assumption can be relaxed by use of a "robust" option.
Hardy-Weinberg平衡的前提下，一个SNP基因型是一个常染色体SNP的两个试验或二项式变量与一个或两个试验为X染色体上的SNP（基于性别而定）。在输入每个SNP"snp.matrix"作为因变量，这个函数首先符合“碱基”Logistic回归模型，然后进行了任期（S）除了得分测试。 Hardy-Weinberg平衡假设使用一个“强有力的”选项可以放宽。
用法----------Usage----------
snp.lhs.tests(snp.data, base.formula, add.formula, subset, snp.subset,
data = sys.parent(), robust = FALSE,
control=glm.test.control(maxit=20, epsilon=1.e-4, R2Max=0.98))
参数----------Arguments----------
参数：snp.data
The SNP data, as an object of class "snp.matrix" or "X.snp.matrix"
SNP数据，如对象类"snp.matrix"或"X.snp.matrix"
参数：base.formula
A formula object describing the base model, with dependent variable omitted
一个formula对象描述的基本模型的因变量，省略
参数：add.formula
A formula object describing the additional terms to be tested, also with dependent variable omitted
一个formula对象描述被测试的附加条款，也与因变量，省略
参数：subset
An array describing the subset of observations to be considered
一个数组，描述观测的子集，被视为
参数：snp.subset
An array describing the subset of SNPs to be considered. Default action is to test all SNPs.
要考虑的一个数组描述的SNPs的子集。默认动作是测试所有的SNPs。
参数：data
The data frame in which base.formula, add.formula and subset are to be evaluated
base.formula，add.formula和subset是被评估的数据框
参数：robust
If TRUE, a test which does not assume Hardy-Weinberg equilibrium will be used
如果TRUE，不承担Hardy-Weinberg平衡测试将使用
参数：control
An object giving parameters for the IRLS algorithm fitting of the base model and for the acceptable aliasing amongst new terms to be tested. See\ codeglm.test.control
对象给予示范碱基IRLS算法拟合和参数之间要测试新条款的接受走样。请参阅\ codeglm.test.control
Details
详情----------Details----------
The tests used are asymptotic chi-squared tests based on the vector of first and second derivatives of the log-likelihood with respect to the parameters of the additional model. The "robust" form is a generalized score test in the sense discussed by Boos(1992). If a data argument is supplied, the snp.data and data objects are aligned by rowname. Otherwise all variables in the model formulae are assumed to be stored in the same order as the columns of the snp.data object.
测试中使用的是基于对数似然第一次和第二次衍生工具方面的额外模型的参数向量上的渐近卡方测试。 “稳健”的形式是在广义的得分测试布斯（1992年）讨论的意义。如果data参数提供，snp.data和data对象由rowname的对齐。否则，所有的模型公式中的变量被假设为在相同的顺序列snp.data对象存储。
值----------Value----------
A data frame containing, for each SNP,
一个数据框，每个SNP，
参数：Chi.squared
The value of the chi-squared test statistic
卡方检验统计量的值
参数：Df
The corresponding degrees of freedom
相应的自由的度
参数：Df.residual
The residual degrees of freedom for the base model; i.e. the number of observations minus the number of parameters fitted
自由的残余度的示范碱基;即减去的安装参数的若干意见
For the logistic model, the base model can, in some circumstances, lead to perfect prediction of some observations (i.e. fitted probabilities of 0 or 1). These observations are ignored in subsequent calculations; in particular they are not counted in the residual degrees of freedom.
Logistic模型，示范碱基，在某些情况下，导致了一些意见的完美预测（即0或1的拟合概率）。在随后的计算这些意见被忽略，尤其是他们不自由的残留度计算。
注意----------Note----------
A factor (or several factors) may be included as arguments to the function strata(...) in the base.formula. This fits all interactions of the factors so included, but leads to faster computation than fitting these in the normal way. Additionally, a cluster(...) call may be included in the base model formula. This identifies clusters of potentially correlated observations (e.g. for members of the same family); in this case, an appropriate robust estimate of the variance of the score test is used.
可以作为函数的参数中包含的一个因素（或几个因素）strata(...)base.formula的。这符合包括所有因素相互作用，但比装修这些在正常的方式，以更快的计算。此外，cluster(...)通话可能被包括在基本模型公式。这标识聚类潜在的相关意见（如为同一家庭的成员），在这种情况下，使用一个合适的得分测试方差稳健估计。
作者（S）----------Author(s)----------
David Clayton <a href="mailto:david.clayton@cimr.cam.ac.uk">david.clayton@cimr.cam.ac.uk</a>
参考文献----------References----------
参见----------See Also----------
glm.test.control,snp.rhs.tests single.snp.tests, snp.matrix-class,
glm.test.control，snp.rhs.testssingle.snp.tests，snp.matrix-class
举例----------Examples----------
data(testdata)
slt1 <- snp.lhs.tests(Autosomes[,1:10], ~cc, ~region, data=subject.data)
print(slt1)
slt2 <- snp.lhs.tests(Autosomes[,1:10], ~strata(region), ~cc,
data=subject.data)
print(slt2)
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 2012-2-25 15:01:25
