metahdep(metahdep)
metahdep()所属R语言包：metahdep
metahdep
metahdep
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Takes a list of metaprep objects and performs the specified meta-analysis on each element. Intended mainly for meta-analyzing the results of multiple gene expression studies.
注意到metaprep对象名单，对每个元素执行指定的荟萃分析。目的主要是多个基因表达研究的荟萃分析结果。
用法----------Usage----------
metahdep(prep.list, genelist = NULL, method = "HBLM", n = 10, m = 10,
center.X = FALSE, delta.split = FALSE, return.list = FALSE,
two.sided = TRUE)
参数----------Arguments----------
参数：prep.list
A list of metaprep class objects as returned by the metahdep.format() function.
metaprep类对象的名单由metahdep.format()函数返回。
参数：genelist
(optional) A subsetting parameter. A vector of gene/probeset names on which to perform the meta-analyses.
（可选）子集参数。一个向量的基因/ probeset名称上进行的荟萃分析。
参数：method
(optional) One of: "FEMA" - fixed effects meta-analysis, "REMA" - random effects meta-analysis, or "HBLM" - hierarchical Bayes linear model. This defaults to "HBLM".
（可选）：“联邦紧急事务管理局” - 固定效应荟萃分析，“磊码” - 随机效应荟萃分析，或“HBLM” - 分层贝叶斯线性模型。这为“HBLM”默认。
参数：n
(optional) An even integer specifying the number of steps to take over each quartile in the numerical integration over tau when doing HBLM. See metahdep.HBLM.
（可选）偶数指定步数超过每头在数值积分四分在做HBLM时。看到metahdep.HBLM。
参数：m
(optional) An even integer specifying the number of steps to take in the numerical integration over varsigma (given tau) when doing HBLM. See metahdep.HBLM.
（可选）偶数指定的步骤，采取在做HBLM时在超过varsigma的数值积分（定头）。看到metahdep.HBLM。
参数：center.X
(optional) A logical value specifying whether or not to center the columns of the covariate matrices. If TRUE, then for the covariate matrix of each metaprep object, the mean each non-intercept column will be subtracted from every element in the column prior to the meta-analysis. This changes the interpretation of the intercept coefficient estimate from the model fit.
（可选）一个逻辑值，指明是否中心的协矩阵列。如果TRUE，然后为每个metaprep对象的协矩阵，平均每个非拦截列，将列中的每个元素中减去之前荟萃分析。这改变截距系数的估计，从模型的拟合解释。
参数：delta.split
(optional) A logical value specifying whether or not to account for hierarchical dependence via delta-splitting. Only used in methods "REMA" and "HBLM". If TRUE, then each metaprep object must include a dependence matrix M.
（可选）一个逻辑值，指明是否通过Delta分裂的层次依赖帐户。只有使用方法“REMA”和“HBLM”。如果TRUE，然后每个metaprep对象必须包括一个依赖矩阵M.
参数：return.list
(optional) A logical value specifying whether to return the results as a list of lists rather than as a data.frame. The default is FALSE.
（可选）一个逻辑值，指明是否返回结果为一个列表，而不是作为一个data.frame。默认FALSE。
参数：two.sided
(optional) A logical value specifying whether to transform the posterior probabilities from the HBLM method. The default TRUE returns 2-sided p-values for the parameter estimates for convenience in interpretation. If this is set to FALSE, then it will return 1-sided posterior probabilities representing P( beta[j] > 0 | data ).
（可选）一个逻辑值，指明是否改造从HBLM方法的后验概率。默认TRUE返回参数估计为方便解释双面p值。如果设置为FALSE，那么它将返回单面代表带够的后验概率（测试[J]> 0 |数据）。
值----------Value----------
Returns a data.frame by default. The exact contents of the data.frame will vary depending on the method argument. The row names of the data.frame will be the gene names from the prep.list argument. For all method options, the first several columns of the resulting data.frame will be the model parameter estimates (beta hats). The next group of columns will be the elements of the variance/covariance matrix for the beta hats. The next group of columns will be the p-values for the parameter estimates. The remaining columns will change depending on the method.
返回一个默认data.frame。的data.frame“确切内容会有所不同取决于method论点。行名称的data.frame“会prep.list参数的基因名称。对于所有的method选项前几列，data.frame的将模型参数估计（β帽子）。下一组列将是方差/协方差矩阵元素的beta帽子。下一组列将参数估计的p值。其余列将改变方法而异。
For FEMA (and REMA), the remaining columns are the Q statistic and its p-value – testing for model homogeneity.
对于联邦紧急事务管理局（REMA），其余各列的Q统计量和p值 - 测试模式同质化。
For HBLM, the remaining columns are the posterior mean and variance of tau, the posterior mean and variance of varsigma, and the posterior covariance of tau and varsigma.
HBLM，其余列后的均值和tau蛋白的变异，后的均值和方差varsigma，头和varsigma的后协方差。
All columns in the data.frame have meaningful names to aid their interpretation.
列在data.frame所有有一个有意义的名字，以帮助他们的解释。
作者（S）----------Author(s)----------
John R. Stevens, Gabriel Nicholas
参考文献----------References----------
from Multiple Microarray Studies, Proceedings of Conference on Applied Statistics in Agriculture, pp. 133-147.
Bioinformatics, 25(19):2619-2620.
Journal of Educational and Behavioral Statistics, 34(1):46-73.
举例----------Examples----------
data(HGU.prep.list)
## do FEMA and REMA, and view the results[＃做的联邦紧急事务管理局和磊码，并查看结果]
FEMA.results <- metahdep(HGU.prep.list, method="FEMA", center.X=TRUE)
head(FEMA.results)
REMA.results <- metahdep(HGU.prep.list, method="REMA", center.X=TRUE)
head(REMA.results)
## get a small subset of genes[＃得到一个小的基因子集。]
## some of these may not be suitable for all methods [＃其中的一些可能不适合所有方法]
## (there may not be enough data for that gene)[＃（该基因可能没有足够的数据）]
data(HGU.newnames)
set.seed(123)
gene.subset <- sample(HGU.newnames$new.name, 50)
## view results from REMA and HBLM with delta splitting on subset of genes[＃查看Delta分裂从REMA及HBLM的结果对基因子集]
REMA.dsplit.results <- metahdep(HGU.prep.list, method="REMA",
genelist=gene.subset, delta.split=TRUE, center.X=TRUE)
head(REMA.dsplit.results)
HBLM.dsplit.results <- metahdep(HGU.prep.list, method="HBLM",
genelist=gene.subset, delta.split=TRUE, center.X=TRUE)
head(HBLM.dsplit.results)
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 2012-2-26 00:42:35
