scanWGassociation(SNPassoc)
scanWGassociation()所属R语言包：SNPassoc
Whole genome association analysis
全基因组关联分析
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function also performs a whole genome association analysis as the function WGassociation but only computes the p values for each SNP corresponding to likelihood ratio test.
此功能也进行全基因组关联分析的功能WGassociation，但只计算每个SNP位点对应的似然比检验的P值。
用法----------Usage----------
scanWGassociation(formula, data, model = c("all"), nperm,
quantitative = is.quantitative(formula, data), genotypingRate = 80)
参数----------Arguments----------
参数：formula
either a symbolic description of the model to be fited (a formula object) without the SNP or the name of response variable in the case of fitting single models (e.g. unadjusted models). It might have either a continuous variable (quantitative traits) or a factor variable (case-control studies) as the response on the left of the ~ operator and terms with additional covariates on the right of the ~. Currently only is possible to write ~1 (that is, non-adjusted analysis). See WGassociation if you are interested in including additional covariates.
无论是象征性的模型来描述fited（公式对象），而不SNP在安装单一车型（如未经调整的机型）的情况下，响应变量的名称。它可能有一个连续变量（数量性状）或一个因素变量（病例对照研究）上的响应左侧额外的协变量的~运营商和条款的权利的~ 。目前仅是可能的写~1（即，非调整分析）。见WGassociation，“如果你有兴趣，包括额外的协变量。
参数：data
a required dataframe of class 'setupSNP' containing the variables in the model and the SNPs
所需的数据框的类的setupSNP“，包含在模型中的变量和单核苷酸多态性
参数：model
a character string specifying the type of genetic model (mode of inheritance) for the SNP. This indicates how the genotypes should be collapsed. Possible values are "codominant", "dominant", "recessive", "overdominant", "log-additive" or "all". The default is "all" that fits the 5 possible genetic models. Only the first words are required, e.g "co", "do", etc.
一个字符串指定类型的遗传模型（模式继承）的SNP。这表明如何倒塌的基因型应。可能的值是“显性”，“显性”，“隐性”，“超显性”，“log添加剂”或“全部”。默认值是“所有”，适合5种可能的遗传模式。只有第一个字是必需的，例如，“合作”，“做”，等等。
参数：nperm
number of permutations to simulate the null hypotesis (e.g OR=1), conditioning on the empirical correlation structure. Only required to perform a permutation test. Currently this test is only available for binary traits.
的排列数来模拟的，空hypotesis（例如：OR = 1）上的经验关系式结构，调理。仅在需要进行置换检验。目前，该测试仅适用于二进制的特征。
参数：quantitative
logical value indicating whether the phenotype (that which is in the left of the operator ~ in 'formula' argument) is quantitative. The function 'is.quantitative' returns FALSE when the phenotype is a variable with two categories (i.e. indicating case-control status). Thus, it is not a required argument but it may be modified by the user.
逻辑值，该值指示是否在“公式”的说法~表型（即是在左侧的运营商）是定量的。的功能“is.quantitative的返回FALSE时，表型是一个变量有两大类（即指示的情况下控制状态）。因此，它是不必需的参数，但它可以由用户修改。
参数：genotypingRate
minimum percentage of genotype rate for a given SNP to be included in the analysis. Default is 80%.
对于一个给定的SNP基因型率最低百分比要包含在分析中。默认值是80％。
值----------Value----------
An object of class 'WGassociation'.
对象的类的WGassociation“。
The function 'print' is used to print the results. The p values are saved in the attribute 'pvalues' as a matrix. They may be obtained using attr(,"pvalues") (see examples). The first column indicates whether a problem with genotyping is present.
使用功能“打印”打印结果。的p值被保存在属性“pvalues作为基质。他们可能获得使用ATTR（中，“pvalues”）（见例子）。第一列表示是否存在的问题，基因分型。
The function 'plot' is used to obtain a plot of p values in the -log scale. See plot.WGassociation for further details
的图“的功能是用来获取中的对数标度的曲线图的p值。有关进一步详情，请参阅plot.WGassociation
参考文献----------References----------
JR Gonzalez, L Armengol, X Sole, E Guino, JM Mercader, X Estivill, V Moreno. SNPassoc: an R package to perform whole genome association studies. Bioinformatics, 2007;23(5):654-5.
参见----------See Also----------
WGassociation getSignificantSNPs association setupSNP plot.WGassociation
WGassociationgetSignificantSNPsassociationsetupSNPplot.WGassociation
实例----------Examples----------
# Next steps may be very time consuming. So they are not executed[下一个步骤可能会花费很长的时间。因此，他们不执行]
#data(HapMap)[数据（人类基因组单体型图）]
#myDat<-setupSNP(HapMap, colSNPs=3:9307, sort = TRUE,[myDat：<-setupSNP（HapMap项目，colSNPs = 3:9307，排序= TRUE，]
# info=HapMap.SNPs.pos, sep="")[信息= HapMap.SNPs.pos，SEP =“”）]
#resHapMap<-scanWGassociation(group~1, data=myDat, model="log")[resHapMap <scanWGassociation（组1，数据= myDat，模型=“log”）]
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 2012-9-30 11:09:37
