R语言 miRNApath包 mirnaTable()函数中文帮助文档(中英文对照)

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mirnaTable(miRNApath)
mirnaTable()所属R语言包：miRNApath

                                         Create miRNA Enrichment Summary Table as data.frame
                                         作为数据框创建miRNA的富集汇总表

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

This function takes an miRNApath object which has been evaluated by runEnrichment(), and provides a data.frame summary.
这个函数需要一个miRNApath对象已由runEnrichment（）评估，并提供了一个数据框的总结。


用法----------Usage----------


mirnaTable(mirnaobj, groups=NULL, format="Tall",
   Significance=0.2, na.char=NA, pvalueTypes=c("pvalues",
   "permpvalues"), maxStringLength=NA)



参数----------Arguments----------

参数：mirnaobj
An object of type mirnapath containing data resulting from the loadmirnapath method.  
包含数据从loadmirnapath方法一个类型mirnapath对象。


参数：groups
List of groups to include in the data.frame, or NULL to include all groups in the miRNApath object.  
组的列表，包括在数据框，或NULL包括所有群体在miRNApath对象。


参数：format
This parameter tells the method to return "Tall", "SuperTall", or "Wide" data. See details below for a description of each format.  
这个参数告诉方法返回“高”，“超高层”，或“宽”的数据。每种格式的描述，详见下文。


参数：Significance
A numerical value specifying the P-value cutoff to use to subset the data returned in the data.frame. To avoid subsetting the data, provide a value of 1.  
一个数值，指定P值的截止使用子集返回的数据在数据框。为了避免子集的数据，提供了价值1。


参数：na.char
Value to use for NA instead of leaving NA as-is, potentially useful for text output.  
值使用NA，而不是离开AS-NA，潜在有用的文本输出。


参数：pvalueTypes
Defines which P-value columns should be returned, more useful for the Wide format which could otherwise have two sets of P-value columns if permutation adjustment were used.  
定义P值列应予以退货，为广泛的格式，否则可能有两套P值列置换调整使用更为有用。


参数：maxStringLength
Defines the maximum length per character string, after being determined by nchar. Strings and column headers are both truncated to this length.  
定义每个字符的字符串的最大长度，确定后nchar。字符串和列标题都截断这个长度。


Details

详情----------Details----------

This function simply combines the various results from the runEnrichment method into one data.frame suitable for plotting or printing in a table. Due to potentially large data volume, the subset feature even when used liberally can substantially reduce the returned dataset size.
这个函数只是简单地结合成一个数据框，适合绘制或打印在一张桌子runEnrichment方法从不同的结果。由于潜在的大数据量，即使当使用宽松的子集功能可以大大减少返回的数据集的大小。

The maxStringLength value is particularly useful, often critical, for displaying a summary table in text format, since pathway names sample group names can be quite long. Although there is no default, a recommended value of 50 seems to fit the appropriate balance of being short enough to fit within a table, and yet be long enough to describe the pathway. The Wide format will contain sample group names as column headers, and a value of 50 should not in theory affect the name, except where it wouldn't be readable in a table anyway.
maxStringLength值是特别有用的，往往是至关重要的，以文本格式显示一个汇总表，因为通路名称样品组名称可能会相当长。虽然没有默认，建议值50似乎更适合短到足以容纳一个表内的适当平衡，还没有足够长的时间来形容的途径。宽幅将包含列标题样本组的名称，和值50在理论上不应该影响但它不会是在一个表中可读反正名。


值----------Value----------

data.frame
数据框

For Tall data, the columns contain P-values and other values useful for discriminating potential hits, the rows contain each miRNA-group combination tested which meets the P-value cutoff. The miRNAs and genes contributing to the enrichment results are concatenated to be summarized in one row and can be rather large.
高大的数据，列包含P值和其他值用于鉴别潜在的点击，行包含每个miRNA组组合测试符合P值截止。富集结果的miRNA和基因串联在一排的总结，并可以相当大。

For SuperTall data, the Tall table as described above is returned, except that the concatenated miRNA-gene values are separated to one row each. Every individual miRNA and gene value is represented on its own row, which can facilitate some summary views or data filtering techniques (e.g. Excel or Spotfire.)
对于超高层数据如上所述，高大表被退回，除了级联的miRNA基因值分开，每个一行。每一个人的miRNA和基因价值代表其自己的行，它可以方便一些总结意见或数据过滤技术（如Excel或Spotfire。）

For Wide data, the columns contain the group names, the rows contain the pathway name, and the cells contain the P-value. Note that the column names will have the P-value column header prepended to the column name, e.g. "pvalue.GroupName".
宽的数据列包含组名称，行包含通路名称，并在单元中含有的P-值。请注意，列名，将有P值前面的列名的列标题，如“pvalue.GroupName。”

An important note when supplying string na.char values, be sure to convert the data to a numeric matrix before calling functions such as heatmap, taking care to remove string values or convert strings to 1.0 beforehand.
一个重要的说明，提供字符串na.char值时，一定到数据转换为数值矩阵，调用功能，如热图之前，删除字符串值，或将字符串转换为1.0事前照顾。


作者（S）----------Author(s)----------


James M. Ward <a href="mailto:jmw86069@gmail.com">jmw86069@gmail.com</a>



参考文献----------References----------

in Alzheimer's disease brain and CSF yields putative  biomarkers and insights into disease pathways, Journal of Alzheimer's Disease 14, 27-41.

参见----------See Also----------

loadmirnapath, filtermirnapath, loadmirnatogene, loadmirnapathways, runEnrichment,
loadmirnapath，filtermirnapath，loadmirnatogene，loadmirnapathways，runEnrichment


举例----------Examples----------


## Start with miRNA data from this package[从这个包＃开始的miRNA数据]
data(mirnaobj);

## Now run enrichment test[＃现在运行铀浓缩试验]
mirnaobj <- runEnrichment( mirnaobj=mirnaobj, Composite=TRUE,
   groups=NULL, permutations=0 );

## Print out a summary table of significant results[＃打印出重大成果汇总表]
finaltable <- mirnaTable( mirnaobj, groups=NULL, format="Tall",
    Significance=0.1, pvalueTypes=c("pvalues") );
finaltable[1:20,];

## Example which calls heatmap function on the resulting data[＃调用所产生的数据热图功能的范例]
widetable <- mirnaTable( mirnaobj, groups=NULL, format="Wide",
    Significance=0.1, na.char=NA, pvalueTypes=c("pvalues") );
## Assign 1 to NA values, assuming they're all equally[＃指定1到NA值，假设他们同样]
## non-significant[＃非显着]
widetable[is.na(widetable)] <- 1;

## Display a heatmap of the result across sample groups[＃显示的结果，整个样本组的热图]
pathwaycol <- mirnaobj@columns["pathwaycol"];
pathwayidcol <- mirnaobj@columns["pathwayidcol"];
rownames(widetable) <- apply(widetable[,c(pathwaycol,
   pathwayidcol)], 1, function(i)paste(i, collapse="-"));
wt <- as.matrix(widetable[3:dim(widetable)[2]], mode="numeric")
heatmap(wt, scale="col");

## Show results where pathways are shared in four or more[＃显示结果在四个或更多的共享途径]
## sample groups[＃样品组]
pathwaySubset <- apply(wt, 1, function(i)
{
   length(i[i < 1]) >= 4;
} )
heatmap(wt[pathwaySubset,], scale="row");

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


注：
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