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R语言 snpStats包 snp.rhs.tests()函数中文帮助文档(中英文对照)

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发表于 2012-2-26 14:48:35 | 显示全部楼层 |阅读模式
snp.rhs.tests(snpStats)
snp.rhs.tests()所属R语言包:snpStats

                                         Score tests with SNP genotypes as independent variable
                                         作为独立变量的SNP基因型的分数测试

                                         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, optionally, one or more potential confounders of a phenotype-genotype association as independent variable. A series of SNPs (or small groups of SNPs) are then tested for additional association with phenotype. In order to protect against misspecification of the variance function,  "robust" tests may be selected.
此功能适合作为因变量,可选一个或多个潜在的混杂因素作为独立变量的表型,基因型协会与表型的广义线性模型。一系列的单核苷酸多态性(或小团体的SNPs),然后测试为额外协会与表型。为了防止误设的方差函数,“稳健”的测试可能被选中。


用法----------Usage----------


snp.rhs.tests(formula, family = "binomial", link, weights, subset, data = parent.frame(),
   snp.data, rules=NULL, tests=NULL, robust = FALSE, uncertain=FALSE,
   control=glm.test.control(maxit=20, epsilon=1.e-5, R2Max=0.999),
   allow.missing=0.01, score=FALSE)



参数----------Arguments----------

参数:formula
The base model formula, with phenotype as dependent variable
基本模型公式型,作为因变量


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 base model is to be fitted
在示范碱基要装的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
An object of class "ImputationRules". If supplied, the rules coded in this object are used, together with snp.data, to calculate tests for imputed SNPs
对象类"ImputationRules"。如果提供,使用,在此对象的编码规则与snp.data,一起估算单核苷酸多态性,计算测试


参数:tests
Either a vector of SNP names (or  numbers) for the SNPs to be tested, or a logical vector of length equal to the number of columns in snp.data, or a list of short numeric or character vectors defining groups of SNPs to be tested (see Details)
无论是向量的单核苷酸多态性SNP的名称(或号码)来进行测试,或定义逻辑向量的长度等于列snp.data的数量,或短的数字或字符向量组的单核苷酸多态性进行测试(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


参数:allow.missing
The maximum proportion of SNP genotype that can be missing before it becomes necessary to refit the base model
SNP基因型的最高比例可以失踪之前,有必要改装示范碱基


参数:score
Is extended score information to be returned?
延长得分要返回的信息?


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). The "base" model is first fitted, and a score test is performed for addition of one or more SNP genotypes to the model. 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).
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。首先安装“碱基”模式,与另外一个或多个单核苷酸多态性基因型模型进行分数测试。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)。

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 used in tests will be referenced by name. However, they can also be referenced by number, a positive number indicating the appropriate column in the input snp.data, and a negative number indicating (minus) a position in the rules list. They can also be referenced by a logical selection vector of length equal to the number of columns in snp.data. Sets of tests involving more than one SNP are referenced by a list and can use a mixture of observed and imputed SNPs. If the tests argument is missing, single SNP tests are carried out; if a rules is given, all imputed SNP tests are calculated, otherwise all SNPs in the input snp.data matrix are tested. But note that, for single SNP tests, the function single.snp.tests will often achieve the same result much faster.
一般单核苷酸多态性在测试中使用的名字将引用。然而,他们也可以被引用数量,正数表明相应的列中输入snp.data,负数表示(减号)在rules列表的位置。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。涉及超过1个SNP的测试集引用列表,并且可以使用一个观测和估算单核苷酸多态性的混合物。如果tests参数丢失,单个SNP的测试进行,如果rules,估算所有SNP的测试计算,否则在输入snp.data矩阵测试所有的SNPs。但要注意的是,单SNP测试,功能single.snp.tests往往会达到同样的效果要快得多。


值----------Value----------

An object of class GlmTests or GlmTestsScore depending on whether score is set to FALSE or TRUE in the call.
一个类的对象GlmTests或GlmTestsScore取决于是否score设置为FALSE或TRUE在通话。


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 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(...)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----------

GlmTests-class, GlmTestsScore-class, single.snp.tests, snp.lhs.tests, impute.snps, ImputationRules-class,
GlmTests-class,GlmTestsScore-class,single.snp.tests,snp.lhs.tests,impute.snps,ImputationRules-class


举例----------Examples----------


data(testdata)
slt3 <- snp.rhs.tests(cc~strata(region), family="binomial",
   data=subject.data, snp.data= Autosomes, tests=1:10)
print(slt3)

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。
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