gseaScores(HTSanalyzeR)
gseaScores()所属R语言包：HTSanalyzeR
Compute enrichment scores for GSEA (Gene Set Enrichment Analysis)
计算的的GSEA富集分数（基因组富集分析）
译者：生物统计家园网 机器人LoveR
描述----------Description----------
'gseaScores' computes the enrichment score, running sum scores and positions of hits for GSEA on one gene set.
“gseaScores计算富集得分，GSEA总和分数和命中的位置上运行的一个基因组。
'gseaScoresBatch' computes enrichment scores for both input 'geneList' and its permutations for GSEA on one gene set.
“gseaScoresBatch”输入“geneList和GSEA一个基因组的排列计算富集分数。
'gseaScoresBatchParallel' computes enrichment scores for both input 'geneList' and their permutations for GSEA on multiple gene sets in parallel.
计算“gseaScoresBatchParallel”两个输入geneList“浓缩分数和GSEA他们在多个基因的排列在平行设置。
用法----------Usage----------
gseaScores(geneList, geneSet, exponent=1, mode = "score")
gseaScoresBatch(geneList, geneNames.perm, geneSet, exponent=1,
nPermutations=1000)
gseaScoresBatchParallel(geneList, geneNames.perm, collectionOfGeneSets,
exponent=1, nPermutations=1000)
参数----------Arguments----------
参数：geneList
a numeric or integer vector of phenotypes in descending or ascending order with elements named by their gene identifiers (no duplicates nor NA values)
（无重复，也不NA值的表型基因标识命名的元素的顺序降序或升序的数字或整数向量）
参数：geneNames.perm
a character matrix including permuted gene identifiers of input 'geneList'. The first column of this matrix should be the gene identifiers of 'geneList', while other columns are vectors of permuted gene identifiers.
一个字符矩阵包括置换输入“geneList”基因标识。这个矩阵的第一列应该“geneList基因标识，而其他列向量置换基因标识。
参数：geneSet
a character vector specifying a gene set (no names, just a vector of characters corresponding to the IDs)
指定一个基因组（没有名字，只是一个矢量字符的ID对应一个字符向量）
参数：collectionOfGeneSets
a list of gene sets. Each gene set in the list is a character vector of gene identifiers
基因组的列表。设置列表中的每个基因是一个基因标识的特征向量
参数：exponent
a single integer or numeric value used in weighting phenotypes in GSEA
在GSEA加权表型的一个整数或数值
参数：nPermutations
a single integer or numeric value specifying the number of permutations for deriving p-values in GSEA
一个整数或数值派生p值在GSEA指定的排列数
参数：mode
a single character value specifying to return only a score (if set as "score"), or all the necessary elements to make a plot (if "graph") (see "gseaPlot" for more details).
一个单一的字符值，指定返回只有一个分数（如果设置为“分数”），或所有必要的元素，使一个图（如“图”）（见“gseaPlot”的更多细节）。
Details
详情----------Details----------
The type of identifiers used in the gene sets and gene list must obviously match.
显然在基因组和基因列表中使用的标识符类型必须匹配。
值----------Value----------
* gseaScores will return:
* gseaScores将返回：
参数：enrichmentScore
a single numeric value of the enrichment score
一个单一的数值浓缩得分
参数：runningScore
a numeric vector of running sum scores (only in mode "graph")
（仅在“图”模式的运行总和分数的数字矢量）
参数：positions
a numeric vector of positions in the ranked phenotype vector of the genes in the gene set (only in mode "graph")
在排名表型向量在基因组的基因位置的数字矢量（只在“图”模式）
* gseaScoresBatch will return a list consisting of:
* gseaScoresBatch将返回一个列表，其中包括：
参数：scoresObserved
a single numeric value of the enrichment score for input 'geneList'
一个单一的数值输入“geneList富集得分
参数：scoresperm
a numeric vector of enrichment scores for permutation tests
数字向量的富集置换测试成绩
* gseaScoresBatchParallel will return a matrix, in which one column is the 'gseaScoresBatch' result for each gene set.
* gseaScoresBatchParallel将返回一个矩阵，其中一列是gseaScoresBatch每个基因组的结果。
作者（S）----------Author(s)----------
Xin Wang, Camille Terfve
参考文献----------References----------
Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S. & Mesirov, J. P. (2005) Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545-15550.
举例----------Examples----------
##example 1[＃示例1]
gl <- runif(100, min=0, max=5)
gl <- gl[order(gl, decreasing=TRUE)]
names(gl) <- as.character(sample(x=seq(from=1, to=100, by=1), size=100,
replace=FALSE))
gs <- sample(names(gl), size=20, replace=FALSE)
##GSEA for input phenotype vector on a single gene set[＃GSEA输入型向量上的一个单一的基因组]
gsea <- gseaScores(geneList=gl, geneSet=gs, mode="score", exponent=1)
##GSEA for both input phenotype vector and permutation tests on a single gene set[＃对输入型向量和一个单一的基因组排列测试GSEA]
nPermutations <- 100
glPerm <- sapply(1:nPermutations, function(n) names(gl)[sample(1:length(gl),
length(gl), replace=FALSE)])
glPerm <- cbind(names(gl), glPerm)
gseaBatch<-gseaScoresBatch(geneList=gl, geneNames.perm=glPerm, geneSet=gs,
nPermutations=100, exponent=1)
##example 2[＃示例2]
## Not run: [＃无法运行：]
library(KEGG.db)
library(org.Dm.eg.db)
library(snow)
##load phenotype vector (see the vignette for details about the[＃负载型向量（见有关细节的小插曲]
##preprocessing of this data set)[＃这组数据的预处理）]
data("KcViab_Data4Enrich")
DM_KEGG <- KeggGeneSets(species="Dm")
##GSEA for input gene list on a single gene set[＃GSEA输入一个单一的基因组的基因列表]
test <- gseaScores(geneList=KcViab_Data4Enrich, geneSet=DM_KEGG[[1]],
exponent=1, mode="graph")
##GSEA for both input gene list and permutation tests on multiple gene[＃GSEA两个输入基因列表和多基因排列测试]
##sets in parallel[＃设置并行]
nPermutations <- 100
glPerm <- sapply(1:nPermutations, function(n) names(KcViab_Data4Enrich)[
sample(1:length(KcViab_Data4Enrich), length(KcViab_Data4Enrich),
replace=FALSE)])
glPerm<-cbind(names(KcViab_Data4Enrich), glPerm)
options(cluster=makeCluster(4,"SOCK"))
gseaBatchPar <- gseaScoresBatchParallel(geneList=KcViab_Data4Enrich,
geneNames.perm=glPerm, collectionOfGeneSets=DM_KEGG[1:10], nPermutations=100,
exponent=1)
if(is(getOption("cluster"),"cluster")) {
stopCluster(getOption("cluster"))
options(cluster=NULL)
}
## 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。
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发表于 2012-2-25 21:55:57
