snp.rhs.estimates(snpStats)
snp.rhs.estimates()所属R语言包：snpStats
Fit GLMs with SNP genotypes as independent variable(s)
适合作为独立的变量（S）的SNP基因型GLMs
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function fits a generalized linear model with phenotype as dependent variable and with a series of SNPs (or small sets of SNPs) as predictor variables. Optionally, one or more potential confounders of a phenotype-genotype association may be included in the model. In order to protect against misspecification of the variance function, "robust" estimates of the variance-covariance matrix of estimates may be calculated in place of the usual model-based estimates.
此功能适合作为因变量与一系列的单核苷酸多态性（或小套的单核苷酸多态性）作为预测变量与表型的广义线性模型。可选的表型，基因型关联的一个或多个潜在的混杂因素可能包括在模型中。为了防止误设的方差函数，“稳健”的估计，估计的方差 - 协方差矩阵可代替通常的基于模型的估计计算。
用法----------Usage----------
snp.rhs.estimates(formula, family = "binomial", link, weights, subset, data
= parent.frame(), snp.data,
rules = NULL, sets = NULL, robust = FALSE, uncertain = FALSE,
control=glm.test.control(maxit=20, epsilon=1.e-5, R2Max=0.999))
参数----------Arguments----------
参数：formula
The model formula, with phenotype as dependent variable and any potential confounders as independent variables. Note that parameter estimates are not returned for these model terms
该模型公式，作为因变量和任何潜在的混杂因素作为自变量的表型。请注意，参数估计不返回这些示范条款
参数：family
A string defining the generalized linear model family. This currently should (partially) match one of "binomial", "Poisson", "Gaussian" or "gamma" (case-insensitive)
一个字符串定义的广义线性模型的家庭。这个目前应该（部分）匹配的"binomial"，"Poisson"，"Gaussian"或"gamma"（不区分大小写）
参数：link
A string defining the link function for the GLM. This currently should (partially) match one of "logit", "log", "identity" or "inverse". The default action is to use the "canonical" link for the family selected
一个字符串定义的GLM的链接功能。这个目前应该（部分）匹配的"logit"，"log"，"identity"或"inverse"。默认的动作是为选定家庭使用的“规范”的链接
参数：data
The dataframe in which the model formula is to be interpreted
在该模型的公式是解释的dataframe
参数：snp.data
An object of class "SnpMatrix" or "XSnpMatrix" containing the SNP data
一个对象的类"SnpMatrix"或"XSnpMatrix"包含的SNP数据
参数：rules
Optionally, an object of class "ImputationRules"
或者，一个对象类"ImputationRules"
参数：sets
Either a vector of SNP names (or numbers) for the SNPs to be added to the model formula, or a logical vector of length equal to the number of columns in snp.data or a list of short vectors defining sets of SNPs to be included (see Details)
无论是向量的单核苷酸多态性SNP的名称（或号码）被添加到模型公式，或逻辑向量的长度等于snp.data列数或短的向量列表定义的SNPs套被列入（见Details）
参数：weights
"Prior" weights in the generalized linear model
“之前”的重量在广义线性模型
参数：subset
Array defining the subset of rows of data to use
定义data使用的行子集的数组
参数：robust
If TRUE, robust tests will be carried out
如果TRUE，健壮的测试将进行
参数：uncertain
If TRUE, uncertain genotypes are used and scored by their posterior expectations. Otherwise they are treated as missing
如果TRUE，不确定的基因型使用后期望取得的。否则，他们被视为失踪
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 glm.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。看到glm.test.control
Details
详情----------Details----------
Homozygous SNP genotypes are coded 0 or 2 and heterozygous genotypes are coded 1. For SNPs on the X chromosome, males are coded as homozygous females. For X SNPs, it will often be appropriate to include sex of subject in the base model (this is not done automatically). The "robust" option causes Huber-White estimates of the variance-covariance matrix of the parameter estimates to be returned. These protect against mis-specification of the variance function in the GLM, for example if binary or count data are overdispersed,
合子SNP的基因型编码0或2杂合子基因型编码1。 X染色体上的SNP位点，编码为纯合子女性的男性。为X个SNPs，它往往会是适当的，包括在示范碱基的主体性（这不是自动完成的）。 “稳健”的选项，使贝尔白参数的协方差矩阵的估计，估计要返回。防止误规范的GLM方差函数，例如，如果二进制或计数数据overdispersed
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.
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。
Usually SNPs to be fitted in models will be referenced by name. However, they can also be referenced by number, indicating the appropriate column in the input snp.data. They can also be referenced by a logical selection vector of length equal to the number of columns in snp.data.
一般单核苷酸多态性在模型拟合将通过名称引用。然而，他们也可以被引用数量，表明相应的列中输入snp.data。它们也可以被引用的逻辑选择向量的长度等于列snp.data的数量。
If the rules argument is supplied, SNPs may be imputed using these rules and included in the model.
如果rules参数提供，单核苷酸多态性可归咎于使用这些规则，并包括在模型中。
值----------Value----------
An object of class GlmEstimates
一个对象的类GlmEstimates
注意----------Note----------
A factor (or several factors) may be included as arguments to the function strata(...) in the 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 parameter estimates 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(...)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，一个适当的参数方差的稳健估计，估计是用来。
If uncertain genotypes (e.g. as a result of imputation) are used, the interpretation of the regression coefficients is questionable; the regression coefficient for an imperfectly measurement of a variable is not a biased (attenuated) estimate of the coefficient of the variable measured.
如果不确定的基因型（例如，作为一个结果归责），回归系数的解释是值得商榷的;不完善测量变量的回归系数是不是有偏见（减毒）测量变量的系数估计。
作者（S）----------Author(s)----------
David Clayton <a href="mailto:david.clayton@cimr.cam.ac.uk">david.clayton@cimr.cam.ac.uk</a>
参见----------See Also----------
GlmEstimates-class, snp.lhs.estimates, snp.rhs.tests,
GlmEstimates-class，snp.lhs.estimates，snp.rhs.tests
举例----------Examples----------
data(testdata)
test <- snp.rhs.estimates(cc~strata(region), family="binomial",
data=subject.data, snp.data= Autosomes, sets=1:10)
print(test)
test2 <- snp.rhs.estimates(cc~region+sex, family="binomial",
data=subject.data, snp.data= Autosomes, sets=1:10)
print(test2)
test.robust <- snp.rhs.estimates(cc~strata(region), family="binomial",
data=subject.data, snp.data= Autosomes, sets=1:10, robust=TRUE)
print(test.robust)
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 2012-2-26 14:48:26
