gageComp(gage)
gageComp()所属R语言包：gage
Compare multiple GAGE analyses results
比较多个压力计分析结果
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function is used to compare the results after running multiple rounds of GAGE analysis. It is frequently used after batch analysis using gagePipe, but may also be used after multiple runs of gage manually.
这个函数是用来运行多个回合的压力计分析比较后的结果。它经常被用于批后使用gagePipe的分析，但也可能多个运行gage手动后使用。
用法----------Usage----------
gageComp(sampnames, dataname, gsname = c("kegg.gs", "go.gs"), use.cols =
c("stat.mean", "q.val"), q.cutoff = 0.1, do.plot = TRUE)
参数----------Arguments----------
参数：sampnames
character vector, the names of the sample groups, on which the GAGE analysis has been done and to be compared. This same argument is used in gagePipe function. These sampnames have been used to label gage result objects.
特征向量，样本组的名称，量具分析已经完成，并进行比较。 gagePipe功能使用此相同的参数。这些sampnames已被用来标记gage结果对象。
参数：dataname
character, the name of the data on which the GAGE analysis has been done. This same argument is used in gagePipe function. This name has be included as the prefix of the GAGE analysis output file names, and will be used in the comparison output file names.
字符，量具分析已经完成了数据的名称。 gagePipe功能使用此相同的参数。这个名字已被列入量具分析输出文件名的前缀，将用于在比较输出文件名。
参数：gsname
character, the name(s) of the gene set collection(s) to be considered in the comparison. In other words, this argument specifies GAGE analysis results with what type(s) of gene sets are to be compared on. Default to be c("kegg.gs", "go.gs").
性格，基因组的集合（S）（S）的名称被认为比较。换句话说，这个参数指定什么类型（S）的基因组相比压力计分析结果。默认为c("kegg.gs", "go.gs")。
参数：use.cols
character, what columns in the gage analysis result objects will be used in the comparison. Default to be "stat.mean" (mean of gene set test statistics) and "q.val" (q-value using BH procedure). Check help information for gage function for more details on the result columns.
字符，哪些列在gage分析结果的对象将在比较中使用。默认是“stat.mean”（指基因组测试统计）和的“q.val”（波黑过程的Q-值）。检查结果列的更多细节，帮助gage功能的信息。
参数：q.cutoff
numeric, q-value cutoff between 0 and 1 for signficant gene sets selection. Default to be 0.1. The same argument is used in gagePipe function.
数字，截止Q值介于0和1 signficant基因设置选择。默认为0.1。 gagePipe功能使用相同的参数。
参数：do.plot
boolean, whether to plot the venn diagram for the comparison results. Default to be TRUE.
布尔，是否绘制维恩图比较结果。默认为TRUE。
Details
详情----------Details----------
gageComp works with the results of gagePipe run by default. Try to load the .RData file named after dataname first. It there is no such file, it assumes that the gage result objects have been loaded and exist in the global environment.
gageComp与gagePipe默认情况下运行的结果。尝试加载的。RDATA文件的命名后dataname第一。它有没有这样的文件，它假定gage结果对象已加载并在全球环境中存在的。
For the GAGE analysis results with each gene set collection specified in gsname, gagePipe compares the signficant gene set lists between the sample groups specified in sampnames. For each gene set collection, three comparisons will be done, on the 2-direction perturbed, up-regulated, and down-regulated gene sets.
对于每个基因组中指定的集合规分析结果gsname，gagePipe在sampnames指定的样本组之间比较signficant基因组列表。对于每个基因组的集合，将三个比较，2方向上的扰动，上调，下调基因组。
The comparison results are output as tab-delimited text files. Venn digrams are only plot for comparison between 2-3 parties. But the text file outputs are not limited by the number of parties under comparison. The venn diagram is generated by calling a revised function based on the VennDigram function from limma package.
比较结果输出为制表符分隔的文本文件。维恩双字母组合只有2-3各方之间的比较图。但不仅限于各方根据比较文本文件输出。维恩图生成调用函数基于从limma包VennDigram功能的修订。
值----------Value----------
The function returns invisible 1 when successfully executed.
成功执行时，该函数返回无形1。
作者（S）----------Author(s)----------
Weijun Luo <luo_weijun@yahoo.com>
参考文献----------References----------
Generally Applicable Gene Set Enrichment for Pathways Analysis. BMC Bioinformatics 2009, 10:161
参见----------See Also----------
gagePipe pipeline for multiple GAGE analysis in a batch; gage the main function for GAGE analysis
gagePipe管道一批多个压力计分析;gage压力计分析的主要功能
举例----------Examples----------
data(gse16873)
cn=colnames(gse16873)
hn=grep('HN',cn, ignore.case =TRUE)
dcis=grep('DCIS',cn, ignore.case =TRUE)
data(kegg.gs)
library(gageData)
data(gse16873.2)
cn2=colnames(gse16873.2)
hn2=grep('HN',cn2, ignore.case =TRUE)
dcis2=grep('DCIS',cn2, ignore.case =TRUE)
#multiple GAGE analysis in a batch with the combined data[在分析与综合数据批处理多个压力计]
gse16873=cbind(gse16873, gse16873.2)
dataname='gse16873' #output data prefix[输出数据的前缀]
sampnames=c('dcis.1', 'dcis.2')
refList=list(hn, hn2+12)
sampList=list(dcis, dcis2+12)
gagePipe(gse16873, gsname = "kegg.gs", dataname = "gse16873",
sampnames = sampnames, ref.list = refList, samp.list = sampList,
comp.list = "paired")
#follow up comparison between the analyses[跟进之间的比较分析]
load('gse16873.gage.RData')
#list gage result objects[列表量具结果对象]
objects(pat = "[.]p$")
gageComp(sampnames, dataname, gsname = "kegg.gs",
do.plot = TRUE)
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 18:23:13
