trioLR(trio)
trioLR()所属R语言包：trio
Trio Logic Regression
三重奏逻辑回归
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Performs a trio logic regression analysis as proposed by Li et al. (2011), where trio logic regression is an adaptation of logic regression (Ruczinski et al., 2003) for case-parent trio data.
李等人提出的，执行三重奏逻辑回归分析。 （2011年），其中三人逻辑回归是一种适应的情况下，父母三人的数据逻辑的回归（Ruczinski等，2003）。
用法----------Usage----------
## Default S3 method:[默认方法]
trioLR(x, y, search = c("sa", "greedy", "mcmc"), nleaves = 5,
penalty = 0, weights = NULL, control=lrControl(), rand = NA, ...)
## S3 method for class 'trioPrepare'
trioLR(x, ...)
## S3 method for class 'formula'[类formula的方法]
trioLR(formula, data, recdom = TRUE, ...)
参数----------Arguments----------
参数：x
either an object of class trioPrepare, i.e. the output of trio.prepare, or a binary matrix consisting of zeros and ones. If the latter, then each column of x must correspond to a binary variable (e.g., codng for a dominant or a recessive effect of a SNP), and each row to a case or a pseudo-control, where each trio is represented by a block of four consecutive rows of x containing the data for the case and the three matched pseudo-controls (in this order) so that the first four rows of x comprise the data for the first trio, rows 5-8 the data for the seocnd trio, and so on. Missing values are not allowed. A convenient way to generate this matrix is to use the function trio.prepare. Afterwards, trioLR can be directly applied to the output of trio.prepare.
无论是类的一个对象trioPrepare，即输出的trio.prepare，或一个二进制矩阵，由零和一。如果是后者，那么每个列x必须对应于一个二进制变量（例如，codng显性或隐性的SNP效果），并且每行的情况下或一个伪控制，其中每个三重奏表示由四个连续的行的块x包含的数据的情况下，三个匹配的伪控制（以该顺序），使得前四行x包括的数据所第一个三重奏，行5-8的seocnd三人的数据，依此类推。遗漏值是不允许的。一个方便的方法来生成这个矩阵是使用的功能trio.prepare。之后，trioLR可以直接应用于输出trio.prepare。
参数：y
a numeric vector specifying the case-pseudo-control status for the observations in x (if x is the binary matrix). Since in trio logic regression, cases are coded by a 3 and pseudo-controls by a 0, y is given by rep(c(3, 0, 0, 0), n.trios), where n.trios is the number of trios for which genotype data is stored in x. Thus, the length of y must be equal to the number of rows in x. No missing values are allowed in y. If not specified, y will be automatically generated.
一个数字矢量指定x（x是二进制矩阵）的意见的情况下，伪控制状态的。因为在三人逻辑回归，情况编码一个3，0的y，其中rep(c(3, 0, 0, 0), n.trios)是一个n.trios和伪控制三重奏的基因型数据被存储在x数目。因此，y的长度必须等于在x的行数。无遗漏值将被允许在y。如果未指定，y将自动生成。
参数：search
character string naming the search algorithm that should be used in the search for the best trio logic regression model. By default, i.e. search = "sa", simulated annealing, the standard search algorithm for a logic regression is used. In this case, depending on the length of nleaves, either one trio logic regression model is fitted or several trio logic regression models of different sizes are fitted. For details, see nleaves. Alternatively, a greedy search can be used by setting search = "greedy", or a MC logic regression analysis (Kooperberg and Ruczinski, 2005) for case-parent trio data can be performed by setting search = "mcmc".
字符串命名的搜索算法，应该使用在寻找最好的三人逻辑回归模型。默认情况下，即search = "sa"，模拟退火算法，逻辑回归标准的搜索算法。在这种情况下的长度，这取决于nleaves，任一个三人的逻辑回归模型是嵌合或几个三人的逻辑回归模型大小不同的嵌合。有关详细信息，请参阅nleaves。可替换地，一个贪婪搜索可用于通过设置search = "greedy"，或MC逻辑回归的分析（Kooperberg和Ruczinski，2005年）为情况父三人组数据可以通过设置search = "mcmc"执行。
参数：nleaves
integer or vector of two integers specifying the maximum number of leaves, i.e.\ variables, in the logic tree of the trio logic regression model (please note in trio logic regression the model consists only of one logic tree). Must be a single integer, if search = "greedy" or search = "mcmc". If search = "sa", it can also be a vector of two integers, where the second integer must be larger than the first one. In this case, several trio logic regression models are fitted in which the maximum numbers of leaves range from nleaves[1] to nleaves[2].
两个整数指定的最大数量三人逻辑回归模型（请注意，在三人逻辑回归模型只包含一个逻辑树）的逻辑树的叶，即\变量，整数或向量。必须是一个整数，如果search = "greedy"或search = "mcmc"。如果search = "sa"，它也可以是一个矢量的两个整数，其中的第二个整数必须大于第一个。在这种情况下，几个三人的逻辑回归模型嵌合在其中的最大数目的叶子范围从nleaves[1]到nleaves[2]。
参数：penalty
a non-negative value for the penalty parameter used in logic regression. The penalty takes the form penalty times the number of leaves in the model. By defaulty, larger models are not penalized. penalty is only relevant when one logic regression model is fitted.
一个非负的penalty参数逻辑回归价值。处罚的形式penalty倍，叶片数在模型中。 defaulty，较大的车型都没有受到惩罚。 penalty是只有当一个逻辑回归模型拟合。
参数：weights
a numeric vector containing one weight for each trio considered in x. Thus, weights must contain nrow(x) / 4 positive values. By default, all trios are equally weighted.
一个数值向量包含一个重量为每三人考虑x。因此，weights必须包含nrow(x) / 4正面的价值观。默认情况下，所有的三重奏是相同的权重。
参数：control
a list of control parameters for the search algorithms and the logic tree considered when fitting a (trio) logic regression model. For these parameters, see lrControl, which is the function that should be used to specify control.
控制参数的搜索算法和逻辑树（三重奏）逻辑回归模型拟合时，会考虑的列表。对于这些参数，请参阅lrControl，这是应该使用的函数，该函数指定control。
参数：rand
integer. If specified, the random number generator will be set into a reproducible state.
整数。如果指定，随机数生成器将被设置成一个可重复的状态。
参数：formula
an object of class formula describing the model that should be fitted.
类formula描述的模式，应安装一个对象。
参数：data
a data frame containing the variables in the model. Each row of data must correspond to an observation, and each column to a binary variable (coded by 0 and 1) or a factor (for details, see recdom) except for the column comprising the response, where no missing values are allowed in data. For a description of the specification of the response, see y.
一个数据框包含在模型中的变量。的每一行data必须符合观察，每列一个二元变量（由0和1的编码）或因子（有关详细信息，请参阅recdom）除列，包括响应，没有缺失值被允许在data。如果在响应的说明书的描述，请参阅y。
参数：recdom
a logical value or vector of length ncol(data) comprising whether a SNP should be transformed into two binary dummy variables coding for a recessive and a dominant effect. If recdom is TRUE (and a logical value), then all factors/variables with three levels will be coded by two dummy variables as described in make.snp.dummy. Each level of each of the other factors (also factors specifying a SNP that shows only two genotypes) is coded by one indicator variable. If recdom isFALSE (and a logical value), each level of each factor is coded by an indicator variable. If recdom is a logical vector, all factors corresponding to an entry in recdom that is TRUE are assumed to be SNPs and transformed into two binary variables as described above. All variables corresponding to entries of recdom that are TRUE (no matter whether recdom is a vector or a value) must be coded either by the integers 1 (coding for the homozygous reference genotype), 2 (heterozygous), and 3 (homozygous variant), or alternatively by the number of minor alleles, i.e. 0, 1, and 2, where no mixing of the two coding schemes is allowed. Thus, it is not allowed that some SNPs are coded by 1, 2, and 3, and others are coded by 0, 1, and 2.
逻辑值或向量的长度ncol(data)包括一个SNP是否应转变为两个二进制编码的隐性和显性效应的虚拟变量。如果recdom是TRUE（和逻辑值），然后所有三个层次的因素/变量将被编码的两个虚拟变量所描述的make.snp.dummy。每一级的每个其他因素（也指定只显示了两个基因型的SNP的因素）编码的一个指标变量。如果recdom是FALSE（和逻辑值），每级各因素的指标变量进行编码。如果recdom是一个逻辑向量，对应的所有因素中的条目recdom，TRUE被认为是个SNP位点，并转化为上述两个二元变量。对应的条目的所有变量recdom是TRUE（无论是否recdom是一个向量或值）必须进行编码，也可以由整数1（编码的纯合子的参考基因型） ，2（杂合子），和3（纯合的变体），或者通过次要等位基因，即0，1和2，其中没有混合的两个编码方案允许的数目。因此，这是不允许的一些SNPs编码由1，2，和3，以及其他的编码由0，1，和2。
参数：...
for the trioPrepare and the formula method, optional parameters to be passed to the low level function trioLR.default, i.e. all arguments of trioLR.default except for x and y. Otherwise, ignored.
低级别的功能trioPrepare，即所有参数的formula的trioLR.default和trioLR.default和x方法，可选的参数被传递到y。否则，忽略不计。
Details
详细信息----------Details----------
Trio logic regression is an adaptation of logic regression to case-parent trio data. Virtually all features for a standard logic regression analysis with the function logreg available in the R package LogicReg are also available for a trio logic regression analysis, either directly via trioLR or via the function trio.permTest for performing permutation tests.
三重奏逻辑回归到情况下母公司三人数据的逻辑回归是一种适应。几乎所有的功能一个标准逻辑回归分析的功能logreg的“可用在R包LogicReg也可用于三重奏逻辑回归分析，可直接通过trioLR通过的功能trio.permTest执行置换测试的。
For a detailed, comprehensive description on how to perform a logic regression analysis, and thus, a trio logic regression analysis, see the Details section of the help page for the function logreg in the R package LogicReg. For a detailed explanation on how to specify the parameters for simulated annealing, see the man page of the function logreg.anneal.control in the R package LogicReg.
对于一个详细，全面的描述如何执行逻辑回归分析，因此，三重奏逻辑回归分析，请参阅Details部分的帮助页面的功能logreg的R 包LogicReg。如何指定参数的模拟退火的详细说明，请参阅手册页的功能logreg.anneal.controlR包LogicReg。
Finally, an example for a trio logic regression analysis is given in the vignette trio available in the R package trio.
最后，三人逻辑回归分析的一个例子中的小插曲trio在R套件“trio。
值----------Value----------
An object of class trioLR composed of the same objects as an object of class logreg. For details, see the Value section of the function logreg from the R package LogicReg.
类的一个对象trioLR相同的对象组成的对象类logreg。有关详细信息，请参阅Value的功能logregR套件“LogicReg部分。
（作者）----------Author(s)----------
Holger Schwender, <a href="mailto:holger.schwender@udo.edu">holger.schwender@udo.edu</a>
参考文献----------References----------
Genetic Epidemiology, 28, 157-170.
Liang, K.Y., Pulver, A.E., and Ruczinski, I. (2010). Detection of SNP-SNP Interactions in Trios of Parents with Schizophrenic Children. Genetic Epidemiology, 34, 396-406.
Graphical Statistics, 12, 475-511.
参见----------See Also----------
logreg, trio.prepare, trio.check, trio.permTest
logreg，trio.prepare，trio.check，trio.permTest
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。
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发表于 2012-10-1 12:07:56
