HTSanalyzeR4cellHTS2(HTSanalyzeR)
HTSanalyzeR4cellHTS2()所属R语言包：HTSanalyzeR
An analysis pipeline for cellHTS2 objects
cellHTS2对象的分析管道
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function writes an html report following a complete analyses of a dataset based on the two classes GSCA (Gene Set Collection Analysis) and NWA (NetWork Analysis) of this package.
这个函数写一个HTML报告，完整的分析，基于这两个类集GSCA（基因组收集分析）和NWA（网络分析）这个包。
用法----------Usage----------
HTSanalyzeR4cellHTS2(
normCellHTSobject,
scoreSign = "-",
scoreMethod = "zscore",
summarizeMethod = "mean",
annotationColumn = "GeneID",
species = "Dm",
initialIDs = "FlybaseCG",
duplicateRemoverMethod = "max",
orderAbsValue = FALSE,
listOfGeneSetCollections,
cutoffHitsEnrichment = 2,
pValueCutoff = 0.05,
pAdjustMethod = "BH",
nPermutations = 1000,
minGeneSetSize = 15,
exponent = 1,
keggGSCs,
goGSCs,
nwStatsControls = "neg",
nwStatsAlternative = "two.sided",
nwStatsTests = "T-test",
nwStatsColumns = c("t.test.pvalues.two.samples", "t.test.pvalues.one.sample"),
nwAnalysisFdr = 0.001,
nwAnalysisGenetic = FALSE,
interactionMatrix = NULL,
nwAnalysisOrder = 2,
ntop = NULL,
allSig = TRUE,
reportDir = "HTSanalyzerReport",
verbose = TRUE
)
参数----------Arguments----------
参数：normCellHTSobject
a normalized, configured and annotated cellHTS object
归一化，配置和的注解cellHTS对象
参数：scoreSign
a single character value specifying the 'sign' argument for the scoring function from cellHTS2 (see 'scoreReplicates')
一个单一的字符值指定为从cellHTS2得分功能的“标志”的说法（见“scoreReplicates”）
参数：scoreMethod
a single character value specifying the 'method' argument for the scoring function from cellHTS2 (see 'scoreReplicates')
一个单一的字符值指定为从cellHTS2得分功能的“法”的说法（见“scoreReplicates”）
参数：summarizeMethod
a summary argument for the summarization function from cellHTS2 (see 'summarizeReplicates')
一个从cellHTS2的汇总函数的总结论点（见“summarizeReplicates”）
参数：annotationColumn
a single character value specifying the name of the column in the fData (cellHTSobject) data frame from which the feature identifiers will be extracted
一个单一的字符值fdata中（cellHTSobject）将提取特征识别数据框中指定列的名称
参数：species
a single character value specifying the species for which the data should be read. The current version supports one of the following species: "Dm" ("Drosophila_melanogaster"), "Hs" ("Homo_sapiens"), "Rn" ("Rattus_norvegicus"), "Mm" ("Mus_musculus"), "Ce" ("Caenorhabditis_elegans").
一个单一的字符值，指定读取数据应种。当前版本支持以下种类之一：“DM”（“Drosophila_melanogaster”），“HS”（“Homo_sapiens”），“RN”（的“Rattus_norvegicus”），“MM”（“ mus_musculus“），”CE“（”Caenorhabditis_elegans）。
参数：initialIDs
a single character value specifying the type of initial identifiers for input 'geneList'. Current version can take one of the following types: "Ensembl.transcript", "Ensembl.prot", "Ensembl.gene", "Entrez.gene", "RefSeq", "Symbol" and "GenBank" for all supported species; "Flybase", "FlybaseCG" and "FlybaseProt" in addition for Drosophila Melanogaster; "wormbase" in addition for Caenorhabditis Elegans.
一个单一的字符值，指定类型为输入“geneList”的初始标识。当前版本可以采取以下几种类型之一：“Ensembl.transcript”，“Ensembl.prot”，“Ensembl.gene”，“Entrez.gene”，“的RefSeq”，“符号”和“ GenBank中“为所有受支持的物种”果蝇“，”FlybaseCG“和”FlybaseProt“除了在果蝇;”wormbase“除了线虫。
参数：duplicateRemoverMethod
a single character value specifying the method to remove the duplicates (should the minimum, maximum or average observation for a same construct be kept). The current version provides "min" (minimum), "max" (maximum), "average" and "fc.avg" (fold change average). The minimum and maximum should be understood in terms of absolute values (i.e. min/max effect, no matter the sign). The fold change average method converts the fold changes to ratios, averages them and converts the average back to a fold change.
一个单一的字符值，指定的方法来删除重复（应保持的最低，最高或平均为同一构造的观察）。目前的版本提供了“MIN”（最小），“最大”（最高），“一般”和“fc.avg”（倍平均变化）。应被理解的最小和最大绝对值（即最小/最大的影响，无论是符号）。倍平均法转换率，平均他们的fold change和转换的平均回褶皱的变化。
参数：orderAbsValue
a single logical value determining whether the values should be converted to absolute value and then ordered (if TRUE), or ordered as they are (if FALSE).
一个单一的逻辑值，决定是否值应转换为绝对值，然后命令（如果为TRUE），或勒令他们（如果为FALSE）。
参数：listOfGeneSetCollections
a list of gene set collections (a 'gene set collection' is a list of gene sets). Even if only one collection is being tested,it must be entered as an element of a 1-element list, e.g. ListOfGeneSetCollections = list(YourOneGeneSetCollection). Naming the elements of listOfGeneSetCollections will result in these names being associated with the relevant data frames in the output (meaningful names are advised)
一个基因组的集合名单（“基因组的集合”是一个基因组的列表）。即使只有一个集合正在测试中，它必须为1元的列表元素，如进入ListOfGeneSetCollections = list(YourOneGeneSetCollection)。命名listOfGeneSetCollections的元素将导致这些名称与输出中的相关数据框（应有意义的名称）
参数：cutoffHitsEnrichment
a single numeric or integer value specifying the cutoff that is used in the definition of the hits for the hypergeometric tests in the over- representation analysis. This cutoff is used in absolute value, since it is applied on scores, i.e. a cutoff of 2 when using z-scores means that we are selecting values that are two standard deviations away from the median of all samples. Therefore, the cutoff should be a positive number.
一个数字或整型值，指定命中超几何中表示过分析测试的定义中使用的截止。截止用于绝对值，因为它是应用上的分数，即截止2，使用Z-分数时表示，我们选择的是两个标准差，远离所有样本的中位数的值。因此，截止应该是一个正数。
参数：pValueCutoff
a single numeric value specifying the cutoff for p-values considered significant
指定一个单一的数值为p-值认为是重要的截止
参数：pAdjustMethod
a single character value specifying the p-value adjustment method to be used (see 'p.adjust' for details)
一个单一的字符值，指定要使用（详见“p.adjust”P-值调整方法）
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：minGeneSetSize
a single integer or numeric value specifying the minimum number of elements in a gene set that must map to elements of the gene universe. Gene sets with fewer than this number are removed from both hypergeometric analysis and GSEA.
一个整数或指定的最低数量的基因组中的元素必须映射到基因宇宙中的元素的数值。从超几何分析和GSEA少于这个数目的基因组被删除。
参数：exponent
a single integer or numeric value used in weighting phenotypes in GSEA (see "gseaScores" function)
一个整数或数值在GSEA加权表型（见“gseaScores”功能）
参数：keggGSCs
a character vector of names of all KEGG gene set collections. This will help create web links for KEGG terms.
特征向量的所有KEGG基因组集合的名称。这将有助于创造为KEGG条款网站链接。
参数：goGSCs
a character vector of names of all GO gene set collections. This will help create web links for GO terms.
特征向量的所有GO基因组的集合名称。这将有助于创造好条件的网页链接。
参数：nwStatsControls
a single character value specifying the name of the controls to be used as a control population in the two-sample tests (this HAS to be corresponding to how these control wells have been annotated in the column "controlStatus" of the fData(cellHTSobject) data frame). If nothing is specified, the function will look for negative controls labelled "neg".
一个单一的字符值，指定控件的名称，用于在这两个样本测试作为控制人口（此相应的是如何将这些控制井已在列的fdata中的“controlStatus”（cellHTSobject注明）数据框）。如果没有指定，该函数将标有“NEG”阴性对照。
参数：nwStatsAlternative
a single character value specifying the alternative hypothesis: "two.sided", "less" or "greater"
一个单一的字符值，指定替代假说：“two.sided的”，“少”或“大”
参数：nwStatsTests
a single character value specifying the tests to be performed: "T-test", "MannWhitney" or "RankProduct". If nothing is specified, all three tests will be performed. Be aware that the Rank Product test is slower than the other two, and returns a percent false discovery (equivalent to a FDR, not a p-value).
一个字符值，指定要执行的测试：“T-检验”，“MannWhitney”或“RankProduct”。如果没有指定，所有这三个测试将被执行。要知道，比其他两个等级产品测试速度较慢，并返回％的错误发现（相当于一个FDR，而不是一个P-值）。
参数：nwStatsColumns
a character vector of any (relevant, i.e. that is produced in the tests) combination of "t.test.pvalues.two.samples", "t.test.pvalues.one.sample", "mannW.test.pvalues.one.sample", "mannW.test.pvalues.two.samples", "rank.product.pfp.greater", "rank.product.pfp.less"
特征向量的任何“t.test.pvalues.two.samples”（相关，即在生产测试）相结合，“t.test.pvalues.one.sample”，“mannW.test。 pvalues.one.sample“，”mannW.test.pvalues.two.samples“，”rank.product.pfp.greater“，”rank.product.pfp.less“
参数：nwAnalysisFdr
a single numeric value specifying the FDR used in the networkAnalysis function for the scores calculation
指定的FDR用一个单一的数值在networkAnalysis功能分数计算
参数：nwAnalysisGenetic
a single logical value indicating if the genetic interaction data of the Biogrid dataset were kept in the network analysis
一个逻辑值，该值指示如果的Biogrid数据集的遗传相互作用数据被保存在网络分析
参数：interactionMatrix
an interaction matrix including columns 'InteractionType', 'InteractorA' and 'InteractorB'. If this matrix is available, the interactome can be directly built based on it.
互动矩阵，包括列的InteractionType，InteractorA和InteractorB“。如果这个矩阵是可用的，可以直接内置相互作用组基础上。
参数：nwAnalysisOrder
the order used in the networkAnalysis function for the scores calculation
成绩计算用于在networkAnalysis函数的顺序
参数：ntop
the number of plots to be produced for the GSEA analysis. For each gene set collection, plots are produced for the "nplots" most significant p-values.
GSEA分析产生的图数量。对于每个基因组的集合，图生产的“nplots”最显着的p值。
参数：allSig
a single logical value indicating whether or not to generate plots for all significant gene sets. A gene set is significant if its corresponding adjusted p-value is less than the pValueCutoff set in function analyze (see function analyze for more details).
一个逻辑值，该值指示是否产生的所有重大的基因组的图。 A基因组是重要的，如果其相应的调整p值比pValueCutoff集功能少analyze（见函数analyze更多细节）。
参数：reportDir
a single character value specifying the directory to store reports
一个单一的字符值，指定的目录来存储报告
参数：verbose
a single logical value indicating to display detailed messages (when verbose= TRUE) or not (when verbose=FALSE)
一个逻辑值，该值指示显示详细消息（VERBOSE = TRUE时）或（当VERBOSE = FALSE）
Details
详情----------Details----------
This pipeline function performs gene set over-representation, enrichment analyses and identifies enriched subnetworks, writes a report and saves results as 'RData' in the user-specified directory.
执行这条管线的功能基因设置了代表性，浓缩分析和子网标识富集，写了一份报告，并保存在用户指定的目录为“RDATA结果。
For the KEGG and GO gene sets, this function produces links to the relevant database entries. To make the report more readable, the user can append a column named 'Gene.Set.Term' to each data frame in the result slot of the object of class GSCA using the method appendGSTerms. To ensure that the function works properly, the gene set ID should comply with the following requirements:
此功能为KEGG和基因集合，生产有关的数据库条目的链接。为了使报告更具可读性，用户可以追加一列名为Gene.Set.Term每一个数据框中的对象类GSCA使用方法appendGSTerms插槽。以确保功能正常工作，基因组标识应当符合下列要求：
for KEGG 3 letters (species ID) followed by a set of numbers and then any number of non-digit characters
KEGG 3个字母（品种编号），由一组数字，然后任意数量的非数字字符
for GO "GO:" immediately followed by the GO term number (digits only) and any number of non-digits characters.
GO“GO：”立即通过GO术语（数字），以及任何非数字字符的数目。
值----------Value----------
Produce a set of html pages and save GSCA and NWA objects. The report starts from the page called "index.html" to navigate those pages.
产生一组HTML页面和保存GSCA和NWA对象。该报告从所谓的“index.html”的页面浏览这些网页。
作者（S）----------Author(s)----------
Camille Terfve, Xin Wang
举例----------Examples----------
## Not run: [＃无法运行：]
library(org.Dm.eg.db)
library(GO.db)
library(KEGG.db)
library(cellHTS2)
library(BioNet)
library(igraph)
#prepare data from cellHTS2[准备从cellHTS2数据]
experimentName <- "KcViab"
dataPath <- system.file(experimentName, package = "cellHTS2")
x <- readPlateList("Platelist.txt", name = experimentName, path=dataPath,
verbose=TRUE)
x <- configure(x, descripFile = "Description.txt", confFile =
"Plateconf.txt",logFile = "Screenlog.txt", path = dataPath)
xn <- normalizePlates(x, scale = "multiplicative", log = FALSE, method =
"median", varianceAdjust = "none")
xn <- annotate(xn, geneIDFile = "GeneIDs_Dm_HFA_1.1.txt",path = dataPath)
cellHTS2DrosoData<-xn
#prepare a list of gene set collections[准备一个基因组的集合列表]
GO_MF <- GOGeneSets(species = "Dm",ontologies = c("MF"))
PW_KEGG <- KeggGeneSets(species = "Dm")
gscList <- list(GO_MF = GO_MF, PW_KEGG = PW_KEGG)
#note: set computer cluster here to do parallel computing[注：集计算机聚类，在这里做并行计算]
#options(cluster=makeCluster(4,"SOCK"))[选项（聚类= makeCluster（4，“袜子”））]
HTSanalyzeR4cellHTS2(
normCellHTSobject=cellHTS2DrosoData,
annotationColumn="GeneID",
species=c("Dm"),
initialIDs="FlybaseCG",
listOfGeneSetCollections=gscList,
cutoffHitsEnrichment=2,
minGeneSetSize=200,
keggGSCs="PW_KEGG",
goGSCs=c("GO_MF"),
allSig=TRUE,
reportDir="HTSanalyzerReport",
verbose=TRUE
)
#note: stop the cluster if you created[注意：停止聚类，如果你创建]
#if(is(getOption("cluster"),"cluster")) {[如果（（getOption（“聚类”），“聚类”））{]
# stopCluster(getOption("cluster"))[stopCluster（getOption（“簇”））]
# options(cluster=NULL)[选项（聚类= NULL）]
#}[}]
##browse the index page[＃浏览索引页]
browseURL(file.path(getwd(), "HTSanalyzerReport", "index.html"))
## 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 21:56:21
