agdex(AGDEX)
agdex()所属R语言包：AGDEX
Agreement of Differential Expression Analysis
协议的差异表达分析
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function performs agreement of differential expression (AGDEX) analysis across a pair of two-group experiments. AGDEX measures and determines the statistical significance of the similarity of the results from two experiments that measure differential expression across two groups. A metric of agreement is defined to measure the similarity and the significance is determined by permutation of group labels. Please see our methodology paper for details [1] (Pounds et al. 2011).
这个函数执行协议的差异表达分析跨一两个组实验（AGDEX）。 AGDEX决定从两个实验测量和措施的差异表达统计学意义的结果相似，在两个组。协议数据定义来衡量的相似性和意义是通过置换组标签决定。细节[1]（英镑等2011），请参阅我们的方法纸。
用法----------Usage----------
agdex(dex.setA, dex.setB, map.data, min.nperms = 100, max.nperms = 10000)
参数----------Arguments----------
参数：dex.setA
A list object with 4 components that defines a two-group comparison "A", for example "human tumor-human control". These components are express.set, comp.def, comp.variable and gset.collection (optional). The express.set component is a Bioconductor ExpressionSet object with a matrix of expression data in exprs and the phenotype data in pData. The comp.variable component gives the name or numeric index of the column of group label in pData of express.set object. comp.def is a string with the format "tumor-control" to define a comparison of expression between samples labeled as "tumor" and samples labeled as "control". The gset.collection (optional) belongs to GeneSetCollection class. See details.
一个有4个组件，定义两个组比较的“A”，例如“人类肿瘤人控制”列表中的对象。这些组件express.set，comp.def，comp.variable和gset.collection（可选）。 express.set组件是与的Bioconductor ExpressionSet对象的表达exprs和在PDATA的表型数据的数据矩阵。 comp.variable组件给PDATA名称或express.set对象组标签列的数字索引。 comp.def是一个字符串格式“肿瘤控制”定义之间的“毒瘤”和“控制”标记的样本标记样本的表现比较。的gset.collection（可选）属于类GeneSetCollection。查看详情。
参数：dex.setB
A list object that defines the other two-group comparison. It has the same structure as dex.setA.
一个列表对象定义其他两个组的比较。它有作为dex.setA的结构相同。
参数：map.data
a list object with 3 components that defines how probe-sets from dex.setA are matched with probe-sets from dex.setB. The probe.map component is a data.frame with each row defining how probe-sets are matched across the pair of two-group comparisons. The components map.Aprobe.col and map.Bprobe.col give the names or numeric index of the column containing probe-set identifiers in dex.setA and dex.setB respectively.
与3个组成部分，它定义如何与从dex.setB探针集匹配探针从dex.setA集列表中的对象。 probe.map组件是与每行定义如何通过对两个组比较匹配的探针集的数据框。给予的名称或数字索引列包含探针集标识符分别在dex.setA和dex.setB组件map.Aprobe.col和map.Bprobe.col的。
参数：min.nperms
minimum number of permutations for adaptive permutation testing of gene-set level results, default is set to 100. Adaptive permutation testing permutes data until observing min.nperms statistics that exceed the observed statistic in absolute value or until max.nperms permutations are performed. Adaptive permutation testing greatly reduces computational effort for permutation analysis in many genomics applications. See [2] (Pounds et al. 2011) for more details.
自适应排列的基因组水平的成果测试排列的最低数量，默认设置为100。自适应置换测试置换，直到观察min.nperms统计，超过绝对值或，直到max.nperms排列进行观察统计数据。自适应排列的测试，大大减少了计算的努力，在许多基因组学应用的置换分析。更多详情请参见[2]（英镑等2011）。
参数：max.nperms
maximum number of permutations for adaptive permutation testing of gene-set level results and fixed total number of permutations for classical permutation testing of probe-set level results and genome-wide agreement of differential expression, default is set to 10000.
自适应检测基因组水平的成果和固定古典置换探针组水平的成果和全基因组差异表达的协议测试的排列总数的排列排列的最大数量，默认设置为10000。
Details
详情----------Details----------
Object express.set belongs to ExpressionSet class. express.set includes two components: exprs: a matrix of gene expression data with row of probe-sets and columns of subjects. pData: a data frame with each row representing a sample and two columns are sample ID and sample group label.
对象express.set属于ExpressionSet类。 express.set包括两部分：exprs：探针台和科目列列的基因表达数据矩阵。 PDATA：与每行代表一个样本的数据框和两列是样品ID和组样品标签。
gset.collection component contains a GeneSetCollection object defined in the Bioconductor package GSEABase. The gset.collection object must be the same identifiers for probe-sets as those used in expression matrix in express.set.
gset.collection组件包含一个GeneSetCollection对象在Bioconductor包GSEABase定义。在gset.collection对象必须是探针集在表达在express.set矩阵使用相同的标识符。
值----------Value----------
A list object with the following components
具有下列组件的列表对象
参数：dex.compA
this string echoes the comp.def component of dex.setA that defines the definition for two-group comparison "A", for example "human tumor-human control"
这个字符串相呼应的dex.setA comp.def组成部分，它定义了两个组比较的“A”的定义，例如，“人类肿瘤人控制”
参数：dex.compB
this string echoes the comp.def component of dex.setB that defines the definition for two-group comparison "B". for example "mouse tumor-mouse control"
这个字符串相呼应dex.setB comp.def的的组件定义为两个组比较，“B”的定义。例如，“小鼠肿瘤鼠标控制”
参数：gwide.agdex.res
a data.frame with the agreement statistics, p-values, and number of permutations for genome-wide agreement of differential expression analysis.
与协议的统计，p值，排列的全基因组的差异表达分析的协议数量的数据框。
参数：gset.res
a data.frame with results of gene-set differential expression analysis for each comparison and gene-set agreement of differential expression analysis results.
每个协议比较和基因组的差异表达分析结果与基因组的差异表达分析结果的数据框。
参数：meta.dex.res
a data.frame with results for probe-sets matched across comparisons "A" and "B". The data.frame includes the differential expression statistic and p-value from each comparison and the meta-analysis z-statistic and p-value for differential expression.
用探针设置的结果数据框跨越比较“A”和“B”的匹配。数据框包含从每个比较差异表达的统计和p值和荟萃分析的Z-统计差异表达的P-值。
参数：dex.resA
a data.frame with differential expression analysis results for individual probe-sets for two-group comparison "A". The data.frame includes the probe-set identifier, difference of mean log-expression statistic, and the p-value.
与个人两个组比较的“A”探测器集的差异表达分析结果的数据框。数据框包括探针集标识符，平均log表达统计差异，p值。
参数：dex.resB
a data.frame with the same structure as dex.resA that gives the results for two-group comparison "B".
具有相同的结构，使两个组比较，“B”的结果作为dex.resA数据框。
参数：dex.asgnA
a data.frame that echoes the group label assignments for comparison "A"
数据框相呼应的比较“一组标签分配
参数：dex.asgnB
a data.frame that echoes the group label assignments for comparison "B"
数据框，呼应对比的“B”组标签分配
参数：gset.listA
a data.frame with gene-set lists for comparison "A". Each row indicates an assignment of a probe-set identifier to a gene-set.
一个比较“A”的基因组列表中的数据框。每一行表示一个基因组的探针集标识符的分配。
参数：gset.listB
a data.frame with gene-set lists for comparison "B".
一个比较“B”的基因组列表中的数据框。
参数：gset.list.agdex
a data.frame that assigns probe-set pairs (probe-sets from comparisons A and B that query the same gene) to gene-sets for gene-set agreement of differential expression analysis.
分配探针组对数据框（探针台从比较A和B，查询相同的基因）基因组基因组差异表达分析的协议。
作者（S）----------Author(s)----------
Stan Pounds <<a href="mailto:stanley.pounds@stjude.org">stanley.pounds@stjude.org</a>; Cuilan Lani Gao <<a href="mailto:cuilan.gao@stjude.org">cuilan.gao@stjude.org</a>>
参考文献----------References----------
A procedure to statistically evaluate agreement of differential expression for cross-species genomics. Bioinformatics doi: 10.1093/bioinformatics/btr362(2011).
Integrated Analysis of Pharmacokinetic, Clinical, and SNP Microarray Data using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing, International Journal of Data Mining and Bioinformatics, 5:143-157.
参见----------See Also----------
ExpressionSet class: ExpressionSet.
ExpressionSet类：ExpressionSet。
GeneSetCollection class: GeneSetCollection.
GeneSetCollection类：GeneSetCollection。
human.data; mouse.data; map.data; gset.data read.agdex.result; write.agdex.result; agdex.scatterplot; get.gset.result.details; write.agdex.gset.details; read.agdex.gset.details
human.data;mouse.data;map.data;gset.dataread.agdex.result;write.agdex.result;agdex.scatterplot;get.gset.result.details;<X >write.agdex.gset.details
举例----------Examples----------
# load data[数据加载]
data(human.data)
data(mouse.data)
data(map.data)
data(gset.data)
# make dex.set object for human data[人类数据dex.set对象]
dex.set.human <- make.dex.set.object(human.data,
comp.var=2,
comp.def="human.tumor.typeD-other.human.tumors",
gset.collection=gset.data)
# make dex.set object for mouse data[鼠标数据对象dex.set]
dex.set.mouse <- make.dex.set.object(mouse.data,
comp.var=2,
comp.def="mouse.tumor-mouse.control",
gset.collection=NULL)
# call agdex routine[调用agdex例行]
res <- agdex(dex.set.human,dex.set.mouse,map.data,min.nperms=5,max.nperms=10)
# see visualization result of the whole genome[看到整个基因组的可视化结果]
agdex.scatterplot(res, gset.id=NULL)
# see visualization result of a specific gene-set[看到一个特定的基因组的可视化结果]
agdex.scatterplot(res, gset.id="DNA_CATABOLIC_PROCESS")
# get the gene-set result of a specific gene-set[得到一个特定的基因组的基因组]
gset.detail <- get.gset.result.details(res, gset.ids="DNA_CATABOLIC_PROCESS", alpha=0.01)
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。
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发表于 2012-2-25 11:31:32
