extractFeatures.R(sdef)
extractFeatures.R()所属R语言包：sdef
Extracting the lists of features of interest
提取感兴趣的功能列表
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function returns the list of features in common using the two suggested rules hmax and h2 (Bayesian model) and additional ones defined by the user.
共同的特点，利用两个建议的规则HMAX和h2（贝叶斯模型）和其他由用户定义的函数返回的列表。
用法----------Usage----------
extractFeatures.R(output.ratio, output.bay, feat.names, h = NULL)
参数----------Arguments----------
参数：output.ratio
The output object from the Frequentist model (ratio function)
The output object from the Frequentist model (ratio function)
参数：output.bay
The output object from the Bayesian model (baymod function)
The output object from the Bayesian model (baymod function)
参数：feat.names
Names of the features (e.g Affy ID for genes)
Names of the features (e.g Affy ID for genes)
参数：h
Additional thresholds in the form of a vector to select a list of features in common. If it is NULL only the Rmax and rule2 are used to select the lists of features of interest
Additional thresholds in the form of a vector to select a list of features in common. If it is NULL only the Rmax and rule2 are used to select the lists of features of interest
Details
详细信息----------Details----------
To select a list of interesting features from the Bayesian model we suggest two decision rules in the paper: 1) the maximum of Median(R(h)) only for the subset of credibility intervals which do not include 1; 2) the largest threshold h for which the ratio R(h) is bigger than 2.
要选择一个有趣的功能列表，贝叶斯模型中，我们提出了两种决策规则的文件：1）最大的中位数（R（H））的子集的可信区间不包括1，2）的最大阈值h为其中的比率R（h）是大于2。
The first one is pointing out the strongest deviation from independence, whilst the second is the largest threshold where the number of features called in common at least doubles the number of features in common under independence. The user can define additional thresholds of interest and obtain the list of associated features.
第一个是指出从独立性最强的偏差，而第二，是世界上最大的阈值，称为共同的特征的数量至少增加一倍的数量在普通的功能下独立。用户可以定义额外的阈值，并获得相关的功能列表中。
值----------Value----------
The function returns an object of the class list. Each element is a matrix where the first column contains the name of the features while the other columns contain the p-values* from the experiments. It also saves a .csv file with the same information.
该函数返回一个对象类的列表。每个元素是一个矩阵，其中第一列中包含的功能，而其他列的名称由实验中所包含的p-值*。这也节省了相同的信息。csv文件。
* instead of the p-values any other measure used to rank the features in the experiments can be used <table summary="R valueblock"> <tr valign="top"><td>max </td> <td> The list of features of interest selected on the basis of the threshold associated to R(hmax)</td></tr> <tr valign="top"><td>rule2 </td> <td> The list of features of interest selected on the basis of the threshold associated to R(h2)</td></tr> <tr valign="top"><td>User</td> <td> The list of features of interest selected on the basis of the additional thresholds selected by the user</td></tr> </table>
*，而不是任何其他措施的p值在实验中用于排序的功能，可用于<table summary="R valueblock"> <tr valign="top"> <TD>max </ TD> <td>在列表中选择所关注的特征的基础上的阈值相关联的R（HMAX）</ TD> </ TR> <tr valign="top"> <TD>rule2 </运输署> <td>在列表中选择所关注的特征的基础上的阈值相关联的R（h2）的</ TD> </ TR> <tr valign="top"> <TD>User</运输署> <td>在列表中选择所关注的特征的基础上，由用户选择的附加阈值</ TD> </ TR> </表>
（作者）----------Author(s)----------
Alberto Cassese, Marta Blangiardo
参考文献----------References----------
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 2012-9-29 23:28:09
