single.snp.tests(snpStats)
single.snp.tests()所属R语言包：snpStats
1-df and 2-df tests for genetic associations with SNPs (or
1-DF和2-DF测试与单核苷酸多态性（或遗传协会
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function carries out tests for association between phenotype and a series of single nucleotide polymorphisms (SNPs), within strata defined by a possibly confounding factor. SNPs are considered one at a time and both 1-df and 2-df tests are calculated. For a binary phenotype, the 1-df test is the Cochran-Armitage test (or, when stratified, the Mantel-extension test). The function will also calculate the same tests for SNPs imputed by regression analysis.
协会之间的表型和系列的单核苷酸多态性（SNP）在可能的混杂因素定义的阶层，此功能进行了测试。 SNPs被认为在一次和两个1-DF和2-DF测试计算。对于一个二进制型，1-DF测试是科克伦 - 阿米蒂奇测试（或，当分层，的曼特尔扩展测试）。该功能也将计算出相同的测试，通过回归分析估算的单核苷酸多态性。
用法----------Usage----------
single.snp.tests(phenotype, stratum, data = sys.parent(), snp.data,
rules=NULL, subset, snp.subset, uncertain = FALSE, score=FALSE)
参数----------Arguments----------
参数：phenotype
A vector containing the values of the phenotype
一个向量，包含的表型值
参数：stratum
Optionally, a factor defining strata for the analysis
或者，定义一个因素的分析阶层
参数：data
A dataframe containing the phenotype and stratum data. The row names of this are linked with the row names of the snps argument to establish correspondence of phenotype and genotype data. If this argument is not supplied, phenotype and stratum are evaluated in the calling environment and should be in the same order as rows of snps
一个dataframephenotype和stratum数据。此行的名称与该行建立的表型和基因型数据通信snps参数名。如果这种说法是不提供的，phenotype和stratum在调用环境评估，并应在同一顺序是snps行
参数：snp.data
An object of class "SnpMatrix" containing the SNP genotypes to be tested
一个类的对象"SnpMatrix"包含的SNP基因型进行测试
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：subset
A vector or expression describing the subset of subjects to be used in the analysis. This is evaluated in the same environment as the phenotype and stratum arguments
一个向量或表达描述子集，在分析中使用的科目。 phenotype和stratum参数，这是在同样的环境评价
参数：snp.subset
A vector describing the subset of SNPs to be considered. Default action is to test all SNPs in snp.data or, in imputation mode, as specified by rules
一个向量描述的SNPs的子集加以考虑。默认动作是测试snp.data或归集模式，所有的SNPs，rules指定
参数：uncertain
If TRUE, uncertain genotypes are handled by replacing score contributions by their posterior expectations. Otherwise they are treated as missing. Setting this option authomatically invokes use of robust variance estimates
如果是TRUE，不确定的基因型处理更换后期望的得分贡献。否则，他们被视为失踪。设置此选项authomatically调用robust方差估计的使用
参数：score
If TRUE, the output object will contain, for each SNP, the score vector and its variance-covariance matrix
如果TRUE，输出对象将包含，每个SNP，得分向量和协方差矩阵
Details
详情----------Details----------
Formally, the test statistics are score tests for generalized linear models with canonical link. That is, they are inner products between genotype indicators and the deviations of phenotypes from their stratum means. Variances (and covariances) are those of the permutation distribution obtained by randomly permuting phenotype within stratum.
正式，检验统计量是广义线性模型与典型环节的得分测试。也就是说，他们是从地层的手段，其表型的基因型指标和偏差之间的内在产品。地层内的表型随机置换获得的排列分布的差异（方差）。
When the function is used to calculate tests for imputed SNPs, the test is still a score test. The score statistics are calculated from the expected value, given observed SNPs, of the score statistic if the SNP to be tested were itself observed.
当函数被用来计算估算单核苷酸多态性测试，测试仍然是一个分数测试。得分统计计算预期值，观察到的单核苷酸多态性的得分统计，如果进行测试SNP本身的观察。
The subset argument can either be a logical vector of length equal to the length of the vector of phenotypes, an integer vector specifying positions in the data frame, or a character vector containing names of the selected rows in the data frame. Similarly, the snp.subset argument can be a logical, integer, or character vector.
subset参数可以是一个逻辑向量的长度等于表型矢量的长度，整数向量，指定data框架，包含所选行的名称或特征向量的位置data框架。同样，snp.subset参数可以是一个逻辑，整数或字符的向量。
值----------Value----------
An object of class "SingleSnpTests". If score is set to TRUE, the output object will be of the extended class "SingleSnpTestsScore" containing additional slots holding the score statistics and their variances (and covariances). This allows meta-analysis using the pool function.
对象类"SingleSnpTests"。如果score设置为TRUE，输出对象将扩展类"SingleSnpTestsScore"持有的得分统计和方差和协的附加插槽。这允许使用pool函数的荟萃分析。
注意----------Note----------
The 1 df imputation tests are described by Chapman et al. (2008) and the 2 df imputation tests are a simple extension of these. The behaviour of this function for objects of class XSnpMatrix is as described by Clayton (2008). Males are treated as homozygous females and corrected variance estimates are used.
查普曼等人1 DF归集测试描述。 （2008年）和2 DF归集测试了这些简单的扩展。这个函数的行为为XSnpMatrix类的对象被描述为克莱顿（2008年）。为纯合子的女性和校正方差估计治疗男性使用。
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----------
Human Heredity, 56:18-31.<br> Clayton (2008) Testing for association on the X chromosome Biostatistics, 9:593-600.)
参见----------See Also----------
snp.lhs.tests, snp.rhs.tests, impute.snps, ImputationRules-class, pool, SingleSnpTests-class, SingleSnpTestsScore-class
snp.lhs.tests，snp.rhs.tests，impute.snps，ImputationRules-class，pool，SingleSnpTests-class，SingleSnpTestsScore-class
举例----------Examples----------
data(testdata)
results <- single.snp.tests(cc, stratum=region, data=subject.data,
snp.data=Autosomes, snp.subset=1:10)
print(summary(results))
# writing to an (anonymous and temporary) csv file[写入csv文件（匿名和临时）]
csvfile <- tempfile()
write.csv(file=csvfile, as(results, 'data.frame'))
unlink(csvfile)
# QQ plot [QQ图]
qq.chisq(chi.squared(results, 1), 1)
qq.chisq(chi.squared(results, 2), 2)
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 14:47:05
