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 hmax rule (Frequentist model).
该函数返回的列表功能共同使用的扬程规则(频率统计模型)。
用法----------Usage----------
extractFeatures.T(output.ratio, feat.names)
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:feat.names
names of the features (e.g Affy ID for genes)
names of the features (e.g Affy ID for genes)
Details
详细信息----------Details----------
To select a list of interesting features from the frequentist model we suggest a decision rules in the paper: the maximum of T(h)=nb genes in common/nb genes in common under the hypothesis of independence. It is pointing out the strongest deviation from independence.
要选择一个有趣的功能列表的频率统计模型中,我们提出一个决策规则的文件:最大的T(H)= NB独立的假设下,普通/ NB的共同基因的基因。据指出独立性最强的偏差。
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 in common selected on the basis of the threshold associated to T(hmax)</td></tr> </table>
*代替p-值用来排名,在试验中的功能,可以使用任何其他措施。 <table summary="R valueblock"> <tr valign="top"> <TD>max </ TD> <td>使用到T相关联的阈值的基础上,选择列表中共同的特点(HMAX )</ TD> </ TR> </ TABLE>