gr.main(geneRecommender)
gr.main()所属R语言包：geneRecommender
A gene recommender algorithm to identify genes coexpressed with a query set of genes
A基因的推荐算法，以确定基因共表达的基因查询集
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function gr.main implements the Gene Recommender algorithm described in Owen et al (2003). Note that in order for gr.main to provide meaningful results, the normalization procedure gr.normalize must first be applied to the gene expression matrix.
功能gr.main实现欧文等人（2003年）中描述的基因导购算法的。请注意，标准化过程为了gr.main提供有意义的结果，gr.normalize必须首先被应用于基因表达矩阵。
用法----------Usage----------
gr.main(normalized.dataset, query, fun = median, ngenes = NULL, extra = FALSE)
参数----------Arguments----------
参数：normalized.dataset
A matrix or ExpressionSet containing the normalized gene expression data. The rows correspond to genes, the columns correspond to experiments, and the entries correspond to the gene expression levels. The rows must be labeled. The values contained in normalized.dataset must be either finite or NA.
一个矩阵或ExpressionSet的，规范化的基因表达数据。列对应的行对应的基因，实验，和条目对应的基因表达水平。必须标明的行。 normalized.dataset中所包含的值必须是有限或不适用。
参数：query
A vector containing the query set of genes. These should correspond to the row names of normalized.dataset. The query must contain at least 2 elements
查询基因组包含的一个向量。这些应符合normalized.dataset行名称。查询必须至少包含2个元素
参数：fun
A function used in choosing the number of experiments to include in the calculation. See below for details.
选择实验的数量，包括在计算中使用函数。细节见下文。
参数：ngenes
The number of genes to return in the result. It's default value is the number of genes found at 50 percent recall.
返回结果中的基因数量。它的默认值是在50％的召回发现的基因数目。
参数：extra
A logical value. When false, the output list will contain only one item, result. When true, several other quantities (listed below) will be calculated and added to the output list.
一个逻辑值。当假，输出列表将包含只有一个项目，result。几个其他数量（如下所列）当为true时，将计算并添加到输出列表。
Details
详情----------Details----------
Given data from a large number of microarray experiments and a query set of genes, which genes have expression profiles that are similar to the query? The Gene Recommender algorithm (Owen et al, 2003) answers this question by first identifying the set of experiments over which the query genes behave similarly. Next, the algorithm ranks all the genes based on the strength of the correlation with the query across the chosen set of experiments.
鉴于从微阵列实验的大量的基因，基因的表达谱，类似查询的查询集的数据？该基因导购算法的欧文等人，（2003）回答这个问题，首先确定的查询基因的表现同样的一组实验。下一步，该算法居所有基因的基础上，整个实验选择集的查询相关的强度。
The algorithm must choose how generous to be in including experiments. How many experiments should be included? The algorithm tries every number of experiments and chooses the number which minimizes a score. In the paper, the score was defined as the median of the ranks of the query genes. In gr.main, the score can be computed with the user-defined function, fun.
该算法必须选择，包括实验是如何大方。应包括多少个实验？该算法尝试每一个实验的数量和选择的数目降到最低得分。的文件，被定义为查询基因的行列中位数得分。 在gr.main，比分可以与用户定义的函数计算，fun。
值----------Value----------
A list containing entries:
一个包含条目的列表：
参数：result
An array of dimensions (ngenes, 2). Column 1 contains the resulting genes, with the highest scoring genes listed first. Column 2 contains character strings, indicating whether the corresponding gene is from the query list or not.
尺寸阵列（ngenes，2）。第1列包含的基因，与先列出得分最高的基因。第2列包含字符串，指示是否从查询列表或不对应的基因是。
参数：fifty.percent.recall
Number of genes found at 50 percent recall.
在50％的召回发现基因的数量。
参数：experiments.included
Experiments included in the analysis.
实验包括在分析中。
参数：experiments.excluded
Experiments excluded from the analysis.
从分析中排除的实验。
参数：s.g.i
An array used as a measure of biological significance for each gene. The output is ranked by this quantity.
数组作为衡量每一个基因的生物学意义。输出的排名是由这个数量。
参数：z.g.i
An array used as a measure of statistical significance for each gene.
一个数组用来作为衡量每一个基因的统计学意义。
参数：contribution
An array indicating the contribution of each experiment to each gene result. For a given gene and a given experiment, the contribution indicates how strongly the experiment suggests that the gene should be high ranking. Using notation from the article, contribution is defined as \bar{Y}_{Q,j} \times Y_{ij}.
一个数组，指示每一个基因的结果，每个实验的贡献。对于一个给定的基因和一个给定的实验，contribution多么强烈的实验表明，该基因应该是高排名。从文章中使用的符号，contribution\bar{Y}_{Q,j} \times Y_{ij}定义。
注意----------Note----------
The results of gr.main will differ from the results generated from the C code released by Owen et al (2003). This is due to differences in the implementation. See the vignette for details.
gr.main结果从欧文等人（2003）公布的C代码产生的结果会有所不同。这是由于在执行的差异。看到细节暗角。
作者（S）----------Author(s)----------
Gregory J. Hather <a href="mailto:ghather@stat.berkeley.edu">ghather@stat.berkeley.edu</a> <br>
with contributions from from Art B. Owen <a href="mailto:art@stat.stanford.edu">art@stat.stanford.edu</a><br>
and Terence P. Speed <a href="mailto:terry@stat.berkeley.edu">terry@stat.berkeley.edu</a>.
参考文献----------References----------
A Gene Recommender Algorithm to Identify Coexpressed Genes in C. elegans. Genome Research 13:1828-1837, 2003.
参见----------See Also----------
gr.normalize, gr.cv
gr.normalize, gr.cv
举例----------Examples----------
#This example uses the geneData dataset from the Biobase package[这个例子使用BIOBASE包geneData集]
data(geneData)
my.query <- c("31730_at", "31331_at", "31712_at", "31441_at")
normalized.data <- gr.normalize(geneData)
gr.main(normalized.data, my.query, ngenes = 10)
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。
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发表于 2012-2-25 18:56:50
