SMVar.paired(SMVar)
SMVar.paired()所属R语言包：SMVar
Structural model for variances with paired data
配对数据的差异的结构模型
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Function to detect differentially expressed genes when data are paired
函数来检测差异表达的基因，当数据是成对的
用法----------Usage----------
SMVar.paired(geneNumbers, logratio, fileexport = NULL, minrep = 2, method = "BH", threshold = 0.05)
参数----------Arguments----------
参数：geneNumbers
Vector with gene names or dataframe which contains all information about spots on the chip
向量的基因名称或数据框，它包含了所有的信息点在芯片上
参数：logratio
matrix with one row by gene and one column by replicate giving the logratio
复制给log比值与一列由基因和一列的矩阵
参数：fileexport
file to export the list of differentially expressed genes
要导出的文件列表中差异表达的基因
参数：minrep
minimum number of replicates to take a gene into account, minrep must be higher than 2
最小数量的复制到考虑到需要的基因，minrep必须是高于2
参数：method
method of multiple tests adjustment for p.values
的多个测试为p.values调整方法
参数：threshold
threshold of False Discovery Rate
虚假发现率阈值
Details
详细信息----------Details----------
This function implements the structural model for variances described in (Jaffrezic et al., 2007). Data must be normalized before calling the function. Matrix geneNumbers must have one of the following formats: "matrix","data.frame","vector","character","numeric","integer".
此功能实现差异（Jaffrezic等，2007年）中描述的结构模型。在调用函数之前，数据必须归。矩阵geneNumbers必须具有以下格式：“矩阵”，“数据框”，“矢”，“性格”，“数字”，“整数”之一。
值----------Value----------
Only the number of differentially expressed genes is printed. If asked, the file giving the list of differentially expressed genes is created
只有差异表达基因的数量被打印出来。如果问列表中差异表达的基因，该文件被创建
If the user creates an object when calling the function (for example "Stat=SMVar.paired(...)") then Stat contains the information for all genes, is sorted by ascending p-values and <table summary="R valueblock"> <tr valign="top"><td>Stat$TestStat </td> <td> gives the test statistics as described in the paper </td></tr> <tr valign="top"><td>Stat$StudentPValue</td> <td> gives the raw p-values</td></tr> <tr valign="top"><td>Stat$DegOfFreedom </td> <td> gives the number of degrees of freedom for the Student distribution for the test statistics</td></tr> <tr valign="top"><td>Stat$LogRatio</td> <td> gives the logratios</td></tr> <tr valign="top"><td>Stat$AdjPValue</td> <td> gives the adjusted p-values</td></tr> </table>
如果用户创建一个对象的时候调用的函数（例如“统计= SMVar.paired的（......）”），然后统计所有基因中包含的信息，是按升序的p值<表摘要=“R valueblock “> <tr valign="top"> <TD>Stat$TestStat </ TD> <TD>给出的检验统计量中所描述的文件</ TD> </ TR> <tr valign="top"> <TD>Stat$StudentPValue </ TD> <TD>给出了原始的p值</ TD> </ TR> <tr valign="top"> <TD> Stat$DegOfFreedom </ TD> < TD>给出的数字为学生分布的检验统计量的自由度</ TD> </ TR> <tr valign="top"> <TD>Stat$LogRatio</ TD> <TD>中给出了对数比</ TD> </ TR> <tr valign="top"> <TD> Stat$AdjPValue </ TD> <TD>给出了调整后的p值</ TD> </ TR> </ TABLE>
注意----------Note----------
If the first column of the file geneNumbers contains identical names for two different spots, these two spots are only counted once if they are both differentially expressed. By default, the correction for multiple testing is Benjamini Hochberg with a threshold of False Discovery Rate (FDR) of 5%. The FDR threshold can be changed, and it is also possible to choose the multiple test correction method ("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none"). To see the references for these methods, use the R-help ?p.adjust.
如果第一列文件geneNumbers包含相同的名称为两个不同的点，这两个点只计算一次，如果他们都差异表达。默认情况下，多重检验校正是Benjamini霍赫贝格错误发现率（FDR）的5％的阈值。的FDR阈值可被改变，并且也可以选择多个测试校正方法（“霍尔姆”，“霍赫贝格”的，“HOMMEL”，“Bonferroni法”，“BH”，“BY”，“FDR”，“无“）。要查看这些方法的参考，使用R-帮助吗？p.adjust。
（作者）----------Author(s)----------
Guillemette Marot with contributions from Anne de la Foye
参考文献----------References----------
实例----------Examples----------
library(SMVar)
data(Spleendata)
attach(Spleendata)
SMVar.paired(SpleenGeneId,SpleenLogRatio)
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 2012-9-30 10:43:48
