runEnrichment(miRNApath)
runEnrichment()所属R语言包：miRNApath
Perform gene set enrichment analysis on a miRNApath
执行上miRNApath富集基因组分析
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This method performs a hypergeometric enrichment analysis on a miRNApath object, which should already contain miRNA data, miRNA-gene associations, gene-pathway associations, and some criteria for filtering miRNA hits from the full tested set.
此方法执行上miRNApath对象的超几何富集分析，这应该已经包含了miRNA的数据，miRNA的基因协会，基因途径商会，和完整的测试集的miRNA命中过滤一些标准。
用法----------Usage----------
runEnrichment(mirnaobj, Composite=TRUE, groups=NULL,
permutations=0)
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：Composite
Defines whether the enrichment treats miRNA-gene as the enriched entity, or uses only the gene.
定义浓缩是否视为丰富实体的miRNA基因，或只使用基因。
参数：groups
List of groups to include in the analysis, although each group is analyzed independent from the other groups.
团体的名单，包括分析，虽然各组进行了分析独立于其他组。
参数：permutations
The number of permutations to use in calculating an adusted P-value. Value of 0 will perform no permutations.
使用一个adusted P值计算的排列数。 0值将不执行排列。
Details
详情----------Details----------
The composite flag indicates whether to treat the fully expanded miRNA-gene combinations as separate enrichment events (TRUE), or whether to treat all effects on one gene as one collective event. The latter case reverts to the classic un-ordered hypergeometric enrichment technique.
复合标志指示是否将其作为独立的铀浓缩活动（TRUE），完全展开的miRNA的基因组合，或是否将作为一个集体活动中的一个基因上的所有效果。后者的情况下恢复到经典联合国有序的超几何富集技术。
However the expansion of combinations is the current method chosen to represent the multiple predicted effects of miRNAs to one gene, and the predicted effect of one miRNA to multiple genes. The algorithm will identify statistically significantly enriched results when the combination of these effects is greater than would be anticipated by random chance.
但是组合的扩展方法，选择代表一个基因的多个miRNA的预测影响，是当前和一个预测的影响多基因的miRNA。该算法将确定统计上的显着丰富的结果，当这些效果的组合是被随机机会比预计的更大。
The adjusted P-value is calculated using the rank of unadjusted P-values divided by the number of permutations minus one (such that the best rank from 1,000 permutations yields an adjusted P-value of 0.001.) The default value 0 was put in place to save time, since most adjustments resulted in stronger "hits" and weaker "non-hits" in terms of pathways enriched. Thus the results are not substantially changed, and permutation adjustment is saved for the final result set.
调整后的P-值计算调整的排列数减一（例如，最好的排名从1000排列得到调整后的P值0.001）。分为P值排名的默认值0到位为了节省时间，因为大多数的调整，更强“点击”和较弱的“非命中”在丰富的途径方面。这样的结果没有实质性改变，置换调整的最终结果集保存。
值----------Value----------
The method returns an object of type mirnapath, a list with components:
该方法返回一个对象，一个组件的列表类型mirnapath：
参数： mirnaTable
data.frame containing the miRNA results data
数据框包含miRNA的结果数据
参数： columns
list containing the names of required column headers associated to the actual column header supplied in the dataset contained in mirnaTable. Required headers: mirnacol, assayidcol, groupcol, filterflagcol.
包含关联到实际列头在包含在mirnaTable数据集提供所需的列头名的名单。所需的标题：mirnacol，assayidcol，groupcol，filterflagcol。
参数： groupcount
The number of groups contained in mirnaTable using the groupcol, if supplied
包含在mirnaTable使用groupcol，如果提供的组数
参数： state
The current state of the object, in this case "enriched".
对象的当前状态，在这种情况下，“丰富”。
参数： mirnaGene
data.frame containing associations between miRNAs and genes.
数据框包含miRNA与基因之间的关联。
参数： mirnaPathways
data.frame containing gene-pathway associations.
数据框包含的基因通路协会。
参数： pathwaycount
Numerical value indicating how many pathways are available in the data, provided for convenience.
数值表示多少途径提供的数据，提供了方便。
参数： filters
List of filters applied to the data, which may include: "P-value", "Fold change", and/or "Expression".
过滤器应用到的数据，其中可能包括：“P值”，“折”的变化，和/或“表达”的名单。
参数： enrichment
Enrichment summary data in the form of a list of elements for each sample group (the sample group is the name of each element.) Each list element is itself a list with enrichment result data for each sample group, as independently calculated: "pvalues" - list of P-values named by pathway ID. "Measured pathway mirnaGenes" - total number of miRNA-gene-pathway combinations measured, which gives some idea of the overall coverage of pathways. The general point is that miRNAs have the potential to cover many genes and pathways. "Total mirnaGenes" - number of miRNA-gene combinations represented in the data. "Enriched pathway mirnaGenes" - number of miRNA-gene values enriched in the pathway tested. "Enriched by miRNA" - list of miRNAs involved in the pathway tested, with the list of genes in parentheses per miRNA. "Enriched by Gene" - same as previous except switching gene and miRNA. "Total enriched mirnaGenes" - the total number of miRNA-gene values involved in any pathway enrichment (significant or not.) The total values are useful when comparing across sample groups, looking particularly for groups with few changes or those with a uniquely high number of changes. Lastly, with permutations > 0 "Permutation P-value" will contain the rank-adjusted P-value as described in the details section.
在每个样本组（样本组的每个元素的名称）的元素的列表的形式浓缩汇总数据的每个列表元素本身就是一个浓缩的结果，作为独立计算每个样本组数据列表：“pvalues” - 通路编号命名的P值列表。 “测量的途径mirnaGenes” - 总数的miRNA基因通路的测量组合，整体覆盖的途径提供了一些想法。一般的一点是，微RNA有可能包括许多基因和途径。的“的共有mirnaGenes” - miRNA的基因组合中的数据代表人数。 “强化的途径mirnaGenes” - 丰富的miRNA基因值在测试通路数。 “丰富的miRNA” - 在测试通路参与miRNA的名单，每个miRNA的括号中的基因列表。 “丰富的基因” - 除交换基因和miRNA以前一样。 “总的丰富mirnaGenes” - 参与任何途径富集（显着或不）的总价值的miRNA的基因值总数是有用的跨样本组进行比较时，寻找一些变化，或具有独特的高，特别是团体数变化。最后，与排列> 0“置换P值”将包含细节部分所述的排名调整后的P值。
参数： pathwayList
Named list of pathways contained in the mirnaobj\$mirnaPathways object, named by the pathway ID values found in the pathwayidcol column. This list facilitates converting the data in the enrichment element to pathway names, since those values are named by the pathway ID to conserve memory.
命名名单在该mirnaobj所载\ $ mirnaPathways对象，途径编号在pathwayidcol列的值的名字命名的途径。这个名单有利于转换的丰富元素的数据通路的名字，因为这些值的途径编号命名，以节省内存。
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
loadmirnapath，filtermirnapath，loadmirnatogene，loadmirnapathways
举例----------Examples----------
## Not run: [＃无法运行：]
## 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 );
## 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：
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。
|
发表于 2012-2-26 01:03:30
