fitBM(PAN)
fitBM()所属R语言包:PAN
Fit a three-beta mixture model to densities of functional gene associations
适合3-β的功能基因研究协会的密度混合模型
译者:生物统计家园网 机器人LoveR
描述----------Description----------
The function fits a three-beta mixture model to densities of functional gene associations computed from rich phenotyping screens.
该功能适合3-β的混合模型,以计算从丰富的表型屏幕的功能基因协会的密度。
用法----------Usage----------
fitBM(object, para=list(zInit=NULL, thetaInit=c(alphaNeg=2, betaNeg=4,
alphaNULL=4, betaNULL=4, alphaPos=4, betaPos=2), gamma=NULL),
ctrl=list(fitNULL=FALSE, tol=1e-3, maxIter=NULL), verbose=TRUE, ...)
参数----------Arguments----------
参数:object
an object of S4 class BetaMixture.
S4类BetaMixture的对象。
参数:para
a list of initial values for parameter estimation in fitting a three-beta mixture model (see 'details').
在装修3-β的混合模型(见“详情”)的初始参数估计值的列表。
参数:ctrl
a list of control parameters for the mixture model fitting (see 'details').
控制参数的混合模型拟合名单(见“详情”)。
参数:verbose
a logical value to switch on (if TRUE) or off if FALSE detailed run-time message.
一个逻辑值切换(如果TRUE)或关闭,如果FALSE详细的运行时的消息。
参数:...
other arguments of the function nlm.
其他参数功能nlm。
Details
详情----------Details----------
This function fits a beta-mixture model to functional gene associations using the Expectation-Maximization algorithm. The function allows various parameter settings to perform fitting by the original (if model='global') or stratified (if model='stratified') beta-mixture model (the model should be specified when creating a new object of BetaMixture).
此功能适合使用期望最大化算法的功能基因协会的β-混合模型。该功能允许各种参数设置进行装修,由原始的(如果模型“全球)或分层(=分层)β-模型的混合模型(模型创造新了BetaMixture的对象时,应指定)。
The initial values of the beta distributions can be set by thetaInit, is a numeric vector including the two shape parameters for the '-' (negative), 'x' (NULL) and '+' (positive) distributions. Please note that if ctrl$NULL is TRUE, meaning that the NULL distribution has already been fitted, then para$alphaNULL and para$betaNULL are supposed to be filled in the estimated NULL parameters by the function fitNULL).
的β分布的初始值可以设置thetaInit,是一个数值向量,包括两个“ - ”(负),X(空)和“+”(阳性)分布的形状参数。请注意,如果ctrl$NULL是TRUE,也就是说,空分布已经被安装,然后para$alphaNULL和para$betaNULL都被认为是填补了NULL参数估计功能fitNULL)。
zInit is a matrix of posterior probabilities for gene associations following the three mixture components.
zInit是一个基因协会的三个混合元件后验概率矩阵。
The hyper-parameters for the dirichlet priors for the mixture components can also be set by para$gamma, which is a numeric matrix with rows and columns correponding to association partitions and the three beta mixture components.
Dirichlet先验的混合组件的超参数也可以设置para$gamma,这是一个协会的分区和三个测试混合组件行和correponding的列的数字矩阵。
The other arguments to control the fitting algorithm are tol and maxIter, which are covergence tolerence and the maximal iterations.
其他参数来控制拟合算法tol和maxIter,这是耐性的收敛性和最大迭代。
Since the estimation of shape parameters of beta distributions are realized by the function nlm numerically, additional arguments for nlm are allowed by ....
由于估计的β分布的形状参数,实现功能nlm数值,nlm...允许额外的参数。
值----------Value----------
This function will return an updated object of class BetaMixture.
这个函数将返回一个更新的对象类BetaMixture。
作者(S)----------Author(s)----------
Xin Wang <a href="mailto:xw264@cam.ac.uk">xw264@cam.ac.uk</a>
参考文献----------References----------
and Florian Markowetz, Posterior association networks and enriched functional gene modules inferred from rich phenotypic perturbation screens, in preparation.
参见----------See Also----------
fitNULL
fitNULL
举例----------Examples----------
## Not run: [#无法运行:]
data(Bakal2007)
bm1<-new("BetaMixture", pheno=Bakal2007, model="global", order=1)
bm1<-fitNULL(bm1, nPerm=10, thetaNULL=c(alphaNULL=4, betaNULL=4),
sumMethod="median", permMethod="all", verbose=TRUE)
bm1<-fitBM(bm1, para=list(zInit=NULL, thetaInit=c(alphaNeg=2, betaNeg=4,
alphaNULL=bm1@result$fitNULL$thetaNULL[["alphaNULL"]],
betaNULL=bm1@result$fitNULL$thetaNULL[["betaNULL"]],
alphaPos=4, betaPos=2), gamma=NULL),
ctrl=list(fitNULL=FALSE, tol=1e-1), verbose=TRUE, gradtol=1e-3)
## End(Not run)[#结束(不运行)]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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