cb_contingency(Category)
cb_contingency()所属R语言包：Category
Create and Test Contingency Tables of Chromosome Band Annotations
创建和测试的染色体带批注的应急表
译者：生物统计家园网 机器人LoveR
描述----------Description----------
For each chromosome band identifier in chrVect, cb_contingency builds and performs a test on a 2 x k contingency table for the genes from selids found in the child bands of the given chrVect element.
对于每一个在chrVect，cb_contingency建立和执行2的XK应急表上为selids在给定的chrVect孩子带发现的基因测试的染色体带标识元素。
cb_sigBands extracts the chromosome band identifiers that were in a contingency table that tested significant given the specified p-value cutoff.
cb_sigBands提取染色体带标识符指定的p值截止测试的应变表。
cb_children returns the child bands of a given band in the chromosome band graph. The argument must have length equal to one.
cb_children返回一个染色体带图带小孩带。参数的长度必须等于一体。
用法----------Usage----------
cb_contingency(selids, chrVect, chrGraph, testFun = chisq.test,
min.expected = 5L, min.k = 1L)
cb_sigBands(b, p.value = 0.01)
cb_children(n, chrGraph)
参数----------Arguments----------
参数：selids
A vector of the selected gene identifiers (usual Entrez IDs).
选定的基因标识（通常Entrez的IDS）的向量。
参数：chrVect
A character vector of chromosome band identifiers
一个染色体带标识符的字符向量
参数：chrGraph
A graph object as returned by makeChrBandGraph. The nodes should be chromosome band IDs and the edges should represent the tree structure of the bands. Furthermore, the graph is expected to have a "geneIds" node attribute providing a vector of gene IDs annotated at each band.
一个graphmakeChrBandGraph对象作为返回。节点应该是染色体带ID和边缘应代表的乐队的树结构。此外，预计将有一个"geneIds"节点的属性，提供一个基因标识标注在每个波段的向量图。
参数：testFun
The function to use for testing the 2 x k contingency tables. The default is chisq.test. It will be called with a single argument, a 2 x k matrix representing the contingency table.
用于测试2 XK应急表中的功能。默认chisq.test。它会被调用带有一个参数，2 XK代表的应变表的矩阵。
参数：min.expected
A numeric value specifying the minimum expected count for columns to be included in the contingency table. The expected count is (rowSum * colSum) / n. Chromosome bands with a select cell count less than min.expected are dropped from the table before testing occurs. If NULL, then no bands will be dropped.
最低的预计数列的一个数值，指定要包括在应急表。预计数是：(rowSum * colSum) / n。一个专责单元的染色体带数比min.expected从表中删除测试之前发生。如果NULL，然后带不会被丢弃。
参数：min.k
An integer giving the minimum number of chromosome bands that must be present in a contingency table in order to proceed with testing.
一个整数，最低数量的染色体带，以进行测试，必须在应急表。
参数：b
A list as returned by cb_contingency
列表作为cb_contingency返回
参数：p.value
A p-value cutoff to use in selecting significant contingency tables.
p值截止到使用选择显著应急表。
参数：n
A length one character vector specifying a chromosome band annotation. Bands not found in chrGraph will return character(0) when passed to cb_children.
指定染色体带注释的长度一个特征向量。乐队没有发现在chrGraph将返回character(0)时，传递到cb_children。
Details
详情----------Details----------
cb_sigBands assumes that the p-value associated with a result of testFun can by accessed as testFun(t)$p.value. We should improve this to be a method call which can then be specialized based on the class of the object returned by testFun.
cb_sigBands假设，P-值与testFun相关可以通过testFun(t)$p.value访问。我们应该提高这是一个方法调用，然后可以基于对象的类专业testFun返回。
值----------Value----------
cb_contingency returns a list with an element for each test performed. This will most often be shorter than length(chrVect) due to skipped tests based on min.found and min.k. Each element of the returned list is itself a list with components:
cb_contingency返回一个列表元素为每个测试。这往往是最短比length(chrVect)由于跳过基于min.found和min.k的测试的。返回列表中的每个元素本身也是一个组件列表：
参数：table
A 2 x k contingency table
2 X的k列联表
参数：result
The output of testFun applied to the table.
的testFun输出应用table。
cb_sigBands returns a character vector of chromosome band identifiers that are in one of the contingency tables that had a p-value less than the cutoff specified by p.value.
cb_sigBands返回一个染色体带标识于一体的应急表有比p.value指定的截止p值的特征向量。
作者（S）----------Author(s)----------
Seth Falcon
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 14:06:05
