adSplit(adSplit)
adSplit()所属R语言包：adSplit
Annotation-Driven Splits
注解驱动的分割
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function searches for annotation-driven splits of patients in microarray data. A split is a partitioning of patients into two groups. In order to do so it refers to GO terms and KEGG pathways. In addition, a significance measure can be computed by simulating a random distribution of scores. DLD-scores are used to judge the quality of a split.
此功能搜索注解驱动的患者在微阵列数据的分割。分裂是分区的患者分为两组。为了做到这一点，它是指以GO术语和KEGG通路。此外，意义的措施，可以通过模拟随机分布的分数计算。DLD分数是用来判断一个分裂的质量。
用法----------Usage----------
adSplit(mydata, annotation.ids, chip.name,
min.probes = 20, max.probes = NULL,
B = NULL, min.group.size = 5, ngenes = 50,
ignore.genes = 5)
参数----------Arguments----------
参数：mydata
either an expression set as defined by the package Biobase or a matrix of expression levels (rows=genes, columns=samples).
无论是一个表达式设置包Biobase或表达水平的矩阵（行=基因，列=样本）的定义。
参数：annotation.ids
a vector of GO or KEGG identifiers in the form "GO:..." or "KEGG:..." respectively. The prefix "KEGG:" is removed from the KEGG-identifiers before accessing the chip's "...PATH2PROBES" hash.
一个好向量或形式KEGG标识符“GO：......”或“KEGG：......”分别。前缀“KEGG：”被删除KEGG标识符之前访问芯片的“...... PATH2PROBES”哈希。
参数：chip.name
the name of the chip by which the expression set is measured. adSplit attempts to load a library of the same name and expects to find a hash called "<chip-name>GO2ALLPROBES" and one called "<chip-name>PATH2PROBES" there.
表达集测量芯片的名称。 adSplit尝试加载一个同名的库，并希望能够找到名为的“<chip-name> GO2ALLPROBES”和一个叫的“<chip-name> PATH2PROBES”有一个哈希。
参数：min.probes
annotation identifiers with fewer than this associated genes are skipped.
少于此相关基因的注释标识符被跳过。
参数：max.probes
annotation identifiers with more than this associated genes are skipped. The default is ten percent of the genes on the chip.
与此相关基因的注释标识符被跳过。默认是10％的芯片上的基因。
参数：B
the number of random gene set samplings to be performed to compute empirical p-values.
基因组随机抽样的数量进行计算经验的p值。
参数：min.group.size
filter criteria to avoid splits suggesting tiny groups. Splits where one of the two suggested groups are smaller than this number are removed from the split set.
筛选条件，以避免分裂，建议小团体。分裂建议两个组都不止这个数较小的分割集移除。
参数：ngenes
number of genes used to compute DLD scores.
DLD分数来计算的基因数目。
参数：ignore.genes
number of best scoring genes to be ignored when computing DLD scores.
最佳得分的基因数目计算DLD分数时被忽略。
Details
详情----------Details----------
This function applies the same splitting procedure to all annotation identifiers provided. Firstly, the associated genes for one identifier are determined and extracted from the expression data. Then the diana2means function is applied to the restricted data and the different splits generated are collected into a single splitSet object.
此功能适用于所有提供的注释标识符相同的分裂过程。首先，确定一个标识符相关基因和表达数据中提取的。然后diana2means功能适用于受限制的数据和不同的分裂生成，收集到一个单一的splitSet对象。
As annotation identifiers vectors of identifiers of the KEGG:nnnnn and GO:nnnnnn are valid. In addition, the keywords "KEGG", "GO" and "all" are allowed, representing all terms in the corresponding ontology.
作为注释标识符标识符KEGG:nnnnn和GO:nnnnnn是有效的向量。此外，关键字“KEGG”，“走出去”和“所有”是允许的，代表相应的本体论中的所有条款。
If B is set to a integer number this number of samplings are used to generate a null-distribution of DLD-scores. This distribution is used to compute empirical p-values for each split. If more than one valid split is found, multiple testing is corrected for by applying Benjamini-Hochbergs correction from the multtest package.
如果B设置一个整数这种取样数量被用来生成一个DLD分数分布的空。这种分布是用来计算每个分割的经验p值。如果多于一个有效的分割，多测试修正通过从multtest包Benjamini-Hochbergs校正。
值----------Value----------
Returns an object of class splitSet with the following list elements:
返回一个类的对象splitSet以下列表中的元素：
参数：cuts
a matrix of split attributions. One row per annotation identifier (GO term or KEGG pathway for which a split has been generated. One column per object in the dataset.
矩阵的分裂归因。一行每注释标识符（GO术语或KEGG通路已经产生分裂。每一个DataSet对象中的列。
参数：score
one score per generated split.
一分，每产生分裂。
参数：pvalue
one empirical p-value per generated split, or NULL
一个经验带够值每产生分裂，或NULL
参数：qvalue
one q-value computed according Benjamini-Hochberg's correction for multiple testing per generated split, or NULL
一个Q值的计算根据Benjamini Hochberg的每产生分裂的多个测试校正，或NULL
作者（S）----------Author(s)----------
Claudio Lottaz, Joern Toedling
参见----------See Also----------
diana2means, randomDiana2means,
diana2means，randomDiana2means
举例----------Examples----------
# prepare data[准备数据]
library(golubEsets)
data(Golub_Merge)
# generate annotation-driven splits for apoptosis and signal transduction[生成注解驱动的分裂单元凋亡和信号转导]
x <- adSplit(Golub_Merge, "GO:0006915", "hu6800")
x <- adSplit(Golub_Merge, c("GO:0007165","GO:0006915"), "hu6800", max.probes=7000)
# generate a split for glutamate metabolism including [生成一个包括谷氨酸代谢分裂]
# an empirical p-value[经验的P-值]
x <- adSplit(Golub_Merge, "KEGG:00251", "hu6800", B=100)
## Not run: [＃无法运行：]
# generate splits for all KEGG pathways.[KEGG通路产生分裂。]
x <- adSplit(Golub_Merge, "KEGG", "hu6800")
image(x)
## 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 11:04:03
