singleGeneCoxph(iterativeBMAsurv)
singleGeneCoxph()所属R语言包：iterativeBMAsurv
Univariate Cox Proportional Hazards Model for selecting top log-ranked predicitve variables
单因素Cox比例风险模型选择顶部登录排名predicitve变量
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This is a univariate technique to rank variables by their predictive relevance for use in survival analysis on microarray data. The log likelihood is computed for each indiviual variable, where a larger
这是一个单变量的排名由他们在微阵列数据的生存分析预测相关变量的技术。对数似然计算每个indiviual变量，其中一个较大的
用法----------Usage----------
singleGeneCoxph(trainData, survData, censoredData)
参数----------Arguments----------
参数：trainData
Data matrix where columns are variables and rows are observations. In the case of gene expression data, the columns (variables) represent genes, while the rows (observations) represent patient samples.
数据矩阵列变量和行观察。在基因表达数据的情况下，列（变量）代表的基因，而行（意见）代表患者样本。
参数：survData
Vector of survival times for the patient samples. Survival times are assumed to be presented in uniform format (e.g., months or days), and the length of this vector should be equal to the number of rows in trainData.
向量的患者样本的存活时间。假设存活时间要统一格式（例如，数月或数天），这个向量的长度应该等于行中trainData的数量。
参数：censoredData
Vector of censor data for the patient samples. In general, 0 = censored and 1 = uncensored. The length of this vector should equal the number of rows in trainData and the number of elements in survData.
向量的患者样本的数据进行审查。在一般情况下，0 =审查，1 =未经审查的。这个向量的长度应该等于在trainData和的元素survData的数量的行的数目。
Details
详情----------Details----------
This function is called by iterateBMAsurv.train.predict.assess.
此功能被称为iterateBMAsurv.train.predict.assess。
值----------Value----------
This function returns a sorted three-column matrix of the training data variables. The first column gives the variable names with the top log-ranked variable appearing first. The second column gives the original indexes of the variables, and the third column gives the rank of the variables from 1 through ncol(trainData). The matrix is
这个函数返回一个训练数据变量的排序三列的矩阵。第一列给出了顶端的log排名变量第一次出现的变量名。第二列给出变量的原始指标，第三列给出的变量从1通过NCOL（trainData）排名。矩阵
参考文献----------References----------
Iterative Bayesian Model Averaging for Survival Analysis. Manuscript in Progress.
Journal of the Royal Statistical Society Series B 34: 187-220.
Bayesian model selection in social research (with Discussion). Sociological Methodology 1995 (Peter V. Marsden, ed.), pp. 111-196, Cambridge, Mass.: Blackwells.
Bayesian Model Averaging in Proprtional Hazard Models: Assessing the Risk of a Stroke. Applied Statistics 46: 433-448.
Bayesian Model Averaging: Development of an improved multi-class, gene selection and classification tool for microarray data. Bioinformatics 21: 2394-2402.
参见----------See Also----------
iterateBMAsurv.train.predict.assess, printTopGenes, trainData, trainSurv, trainCens
iterateBMAsurv.train.predict.assess，printTopGenes，trainData，trainSurv，trainCens
举例----------Examples----------
library(BMA)
library(iterativeBMAsurv)
data(trainData)
data(trainSurv)
data(trainCens)
sorted.genes <- singleGeneCoxph(trainData, trainSurv, trainCens)
## Write top 100 genes to file[＃写提交的前100个基因。]
sorted.top.genes <- printTopGenes(retMatrix=sorted.genes, 100, trainData)
## The file, 'sorted_topCoxphGenes_100', is now in the working R directory.[＃文件，“sorted_topCoxphGenes_100，现在是在r目录的工作。]
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 2012-2-25 22:44:45
