tabulate.top.dep.features(SIM)
tabulate.top.dep.features()所属R语言包：SIM
Lists the P-values for the dependent features
列出了相关的功能的P-值
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Lists the integrated analysis P-values for the dependent features in the analyzed regions, together with the available annotation.
列出在分析区域相关功能的综合分析，P值，加上可用的注解。
用法----------Usage----------
tabulate.top.dep.features(input.regions = "all chrs",
adjust.method="BY",
method = c("full", "smooth", "window", "overlap"),
significance = 1,
run.name = "analysis_results")
参数----------Arguments----------
参数：input.regions
vector indicating the dependent regions to be analyzed. Can be defined in four ways: 1) predefined input region: insert a predefined input region, choices are: “all chrs”, “all chrs auto”, “all arms”, “all arms auto” In the predefined regions “all arms” and “all arms auto” the arms 13p, 14p, 15p, 21p and 22p are left out, because in most studies there are no or few probes in these regions. To include them, just make your own vector of arms. 2) whole chromosome(s): insert a single chromosome or a list of chromosomes as a vector: c(1, 2, 3). 3) chromosome arms: insert a single chromosome arm or a list of chromosome arms like c("1q", "2p", "2q"). 4) subregions of a chromosome: insert a chromosome number followed by the start and end position like "chr1:1-1000000" These regions can also be combined, e.g. c("chr1:1-1000000","2q", 3). See integrated.analysis for more information.
vector表明依赖区域进行分析。可以定义在四个方面：1) predefined input region: 插入一个预定义的输入区域，选择是：“所有CHRS”，“所有CHRS汽车”，“武器”，“所有武器的汽车”在预定区域“所有武器”和“所有自动武器”的武器，13P，14P，15P，21P和22P冷落，因为在大多数研究中，有没有在这些区域或几个探针。包括他们，才使自己的武器向量。 2) whole chromosome(s): 插入一个vector:c(1, 2, 3)的一个单一的染色体或染色体列表。 3) chromosome arms: 插入一个单一的染色体或染色体臂像c("1q", "2p", "2q")名单。 4) subregions of a chromosome: 插入一个染色体数目的开始和结束位置，如"chr1:1-1000000"这些区域也可以结合，如c("chr1:1-1000000","2q", 3)。看到integrated.analysis更多信息。
参数：adjust.method
Method used to adjust the P-values for multiple testing, see p.adjust. Default is “BY” recommended when copy number is used as dependent data. See SIM for more information about adjusting P-values.
用于调整多个测试P值的方法，看到p.adjust“。默认是“加”拷贝数时，建议使用相关数据。关于调整P值的更多信息，请参阅SIM卡。
参数：method
this must be the either one of “full”, “window”, “overlap” or “smooth” but the data should generated by the same method in integrated.analysis.
这必须是“充分”的一个“窗口”，“重叠”或“平稳”，但数据应产生同样的方法在integrated.analysis。
参数：significance
threshold used to select the significant dependent features. Pvalues below this threshold will be used to estimate regions.
阈值用来选择显着的相关功能。低于此阈值将被用来估算pvalues区域。
参数：run.name
This must be the same a given to integrated.analysis
这必须是相同的一个给定的integrated.analysis
Details
详情----------Details----------
Output is a .txt file containing a table with sorted integrated analysis P-values of the dependent features. It includes the ann.dep columns that were read in the assemble.data function. Additionally it returns a .txt file containing the significant P-value rich regions. No P-value rich regions are returned when zscores.diag = "all".
输出是包含排序的综合分析P值的相关功能表。txt文件。它包括了ann.dep读在assemble.data功能列。此外，它返回一个。txt文件，其中包含了显着的P-值丰富的区域。没有丰富的区域，P值时返回zscores.diag = "all"。
值----------Value----------
Returns a list of data.frame's for each input region. Significant P-value rich regions are returned as a data.frame. This data.frame can be used as an input for getoverlappingregions. Additionally, the results are stored in a subdirectory of run.name as txt.
返回为每个输入区域的list的data.frame。显著P值的丰富的区域返回data.frame的。这个数据框，可以用来作为输入getoverlappingregions。此外，结果存储在run.name为txt子目录。
作者（S）----------Author(s)----------
Marten Boetzer, Melle Sieswerda, Renee X. de Menezes <a href="mailto:R.X.Menezes@lumc.nl">R.X.Menezes@lumc.nl</a>
参见----------See Also----------
SIM, tabulate.pvals, tabulate.top.indep.features
SIM卡，tabulate.pvals，tabulate.top.indep.features
举例----------Examples----------
#first run example(assemble.data)[第一次运行的例子（assemble.data）]
#and example(integrated.analysis)[和例如（integrated.analysis）]
#get the top dependent features sorted by p-value[得到p值排序前相关的功能]
table.dep <- tabulate.top.dep.features(input.regions="8q",
adjust.method="BY",
method="full",
significance=0.05,
run.name="chr8q")
head(table.dep[["8q"]])
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 2012-2-26 14:24:56
