calculate.NGSk(sigPathway)
calculate.NGSk()所属R语言包：sigPathway
Calculate NGSk (NTk-like) statistics with gene label permutation
NGSk（NTK类）统计计算与基因标签排列
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Calculates the NGSk (NTk-like) statistics with gene label permutation and the corresponding p-values and q-values for each selected pathway.
计算与基因标签置换NGSk（NTK状）统计数据和相应的p值和Q值，为每个选定的途径。
用法----------Usage----------
calculate.NGSk(statV, gsList, nsim = 1000, verbose = FALSE,
alwaysUseRandomPerm = FALSE)
参数----------Arguments----------
参数：statV
a numeric vector of test statistic (not p-values) for each individual probe/gene
检验统计量（p值）的数字为每个探针/基因向量
参数：gsList
a list containing three vectors from the output of the selectGeneSets function
一个列表，其中包含三个向量从selectGeneSets函数的输出，
参数：nsim
an integer indicating the number of permutations to use
一个整数，指示的使用数量排列
参数：verbose
a boolean to indicate whether to print debugging messages to the R console
一个布尔值，指示是否打印调试消息的R控制台
参数：alwaysUseRandomPerm
a boolean to indicate whether the algorithm can use complete permutations for cases where nsim is greater than the total number of unique permutations possible with the phenotype vector
一个布尔值，表明该算法是否可以使用完整的情况排列nsim是phenotype向量大于独特的排列总数可能
Details
详情----------Details----------
This function is a generalized version of NTk calculations; calculate.NTk calls this function internally. To use this function, the user must specify a vector of test statistics (e.g., t-statistic, Wilcoxon). Pathways from this function can be ranked with rankPathways.NGSk or with rankPathways when combined with results from another pathway analysis algorithm (e.g., calculate.NEk).
此功能的NTK计算的广义版本;calculate.NTk内部调用这个函数。要使用此功能，用户必须指定一个检验统计量的向量（例如，t-统计量，秩）。从这个函数的途径排名可以用rankPathways.NGSk或rankPathways时，与从其他途径分析算法的结果相结合（例如，calculate.NEk）。
值----------Value----------
A list containing
一份列表，列出
参数：ngs
number of gene sets
基因组数
参数：nsim
number of permutations performed
数进行排列
参数：t.set
a numeric vector of Tk/Ek statistics
TK / EK统计的数字向量
参数：t.set.new
a numeric vector of NTk/NEk statistics
NTK / NEK统计的数字向量
参数：p.null
the proportion of nulls
空值的比例
参数：p.value
a numeric vector of p-values
数字向量的p值
参数：q.value
a numeric vector of q-values
数字向量的Q值
作者（S）----------Author(s)----------
Lu Tian, Peter Park, and Weil Lai
参考文献----------References----------
P.J. (2005) Discovering statistically significant pathways in expression profiling studies. Proceedings of the National Academy of Sciences of the USA, 102, 13544-9.
举例----------Examples----------
## Load in filtered, expression data[＃加载在过滤数据，表达]
data(MuscleExample)
## Prepare the pathways to analyze[＃准备的途径分析]
probeID <- rownames(tab)
gsList <- selectGeneSets(G, probeID, 20, 500)
nsim <- 1000
ngroups <- 2
verbose <- TRUE
weightType <- "constant"
methodName <- "NGSk"
npath <- 25
allpathways <- FALSE
annotpkg <- "hgu133a.db"
statV <- calcTStatFast(tab, phenotype, ngroups)$tstat
res.NGSk <- calculate.NGSk(statV, gsList, nsim, verbose)
## Summarize top pathways from NGSk[＃总结从NGSk顶端途径。]
res.pathways.NGSk <-
rankPathways.NGSk(res.NGSk, G, gsList, methodName, npath)
print(res.pathways.NGSk)
## Get more information about the probe sets' means and other statistics[＃获取更多探针集的手段和其他统计信息]
## for the top pathway in res.pathways.NGSk[＃为在res.pathways.NGSk顶部途径]
gpsList <-
getPathwayStatistics.NGSk(statV, probeID, G, res.pathways.NGSk$IndexG,
FALSE, annotpkg)
print(gpsList[[1]])
## Write table of top-ranked pathways and their associated probe sets to[＃写表和世界排名第一的途径及其相关的探针设置]
## HTML files[＃HTML文件]
parameterList <-
list(nprobes = nrow(tab), nsamples = ncol(tab),
phenotype = phenotype, ngroups = ngroups,
minNPS = 20, maxNPS = 500, ngs = res.NGSk$ngs,
nsim.NGSk = res.NGSk$nsim,
annotpkg = annotpkg, npath = npath, allpathways = allpathways)
writeSP(res.pathways.NGSk, gpsList, parameterList, tempdir(),
"sigPathway_cNGSk", "TopPathwaysTable.html")
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 2012-2-26 14:16:55
