deds.stat.linkC(DEDS)
deds.stat.linkC()所属R语言包：DEDS
Differentail Expression via Distance Summary of Multiple Statistics
分析微分方程，通过远程多元统计摘要的表达
译者：生物统计家园网 机器人LoveR
描述----------Description----------
deds.stat.linkC integrates different statistics of differential expression (DE) to rank and select a set of DE genes.
deds.stat.linkC集成了不同的统计差异表达（DE）的排名和选择一套DE的基因。
用法----------Usage----------
deds.stat.linkC(X, L, B = 1000, tests = c("t", "fc", "sam"), tail =
c("abs", "lower", "higher"), extras = NULL, distance = c("weuclid",
"euclid"), adj = c("fdr", "adjp"), nsig = nrow(X), quick = TRUE)
参数----------Arguments----------
参数：X
A matrix, with m rows corresponding to variables (hypotheses) and n columns corresponding to observations. In the case of gene expression data, rows correspond to genes and columns to mRNA samples. The data can be read using read.table.
与m行相应的变量（假设）和n列对应的观察矩阵。在基因表达数据的情况下，行对应mRNA样品的基因和列。可以读取数据，使用read.table。
参数：L
A vector of integers corresponding to observation (column) class labels. For k classes, the labels must be integers between 0 and k-1.
观察（列）类的标签对应的整数向量。对于k类，标签必须是0k-1之间的整数。
参数：B
The number of permutations. For a complete enumeration, B should be 0 (zero) or any number not less than the total number of permutations.
排列数。对于一个完整的枚举，B应该是0（零）或任何数量不超过总数的排列。
参数：tests
A character vector specifying the statistics to be used to test the null hypothesis of no association between the variables and the class labels, test could be any of the following: <br> <table summary="Rd table"> <tr> <td align="left"> "t": </td><td align="left"> one or two sample t-statistics; </td> </tr> <tr> <td align="left"> "f": </td><td align="left"> F-statistics;</td> </tr> <tr> <td align="left"> "fc": </td><td align="left"> fold changes among classes;</td> </tr> <tr> <td align="left"> "sam":</td><td align="left"> SAM-statistics; </td> </tr> <tr> <td align="left"> "modt": </td><td align="left"> moderated t-statistics; </td> </tr> <tr> <td align="left"> "modt": </td><td align="left"> moderated F-statistics; </td> </tr> <tr> <td align="left"> "B": </td><td align="left"> B-statistics.</td> </tr> </table>
字符向量指定被用来测试的变量和类的标签之间没有关联的零假设的统计，test可能是下列任何：参考<table summary="Rd table">。< TR> <td ALIGN="LEFT">"t"：</ TD> <td ALIGN="LEFT">一个或两个样本t-统计量; </ TD> </ TR> <TR> <TD对齐=“左”>"f"：</ TD> <td ALIGN="LEFT"> F-统计; </ TD> </ TR> <TR> <TD ALIGN="LEFT">"fc" ：</ TD> <td ALIGN="LEFT">类之间的fold change; </ TD> </ TR> <TR> <TD ALIGN="LEFT">"sam"：</ TD> <TD ALIGN =“左”的> SAM统计; </ TD> </ TR> <TR> <TD ALIGN="LEFT">"modt"：</ TD> <td ALIGN="LEFT">放缓T-统计; </ TD> </ TR> <TR> <TD ALIGN="LEFT">"modt"：</ TD> <td ALIGN="LEFT">放缓F-统计; </ TD> </ TR> <TR> <td ALIGN="LEFT">"B"：</ TD> <TD ALIGN="LEFT">的B-统计</ TD> </ TR> </ TABLE>
参数：tail
A character string specifying the type of rejection region.<br> If side="abs", two-tailed tests, the null hypothesis is rejected for large absolute values of the test statistic.<br> If side="higher", one-tailed tests, the null hypothesis is rejected for large values of the test statistic.<br> If side="lower", one-tailed tests, the null hypothesis is rejected for small values of the test statistic.
如果一个字符串指定排斥区域类型。参考如果side="abs"，一个side="higher"，双尾检验，检验统计量的大绝对值拒绝零假设。参考尾检验，零假设被拒绝的检验统计量的大值。如果side="lower"，单尾测试参考，拒绝零假设检验统计量的小值。
参数：extras
Extra parameter needed for the test specified; see deds.genExtra.
需要额外的参数指定的测试;看到deds.genExtra。
参数：distance
A character string specifying the type of distance measure used for the calculation of the distance to the extreme point (E). <br> If distance="weuclid", weighted euclidean distance, the weight for statistic t is 1/MAD(t); <br> If distance="euclid", euclidean distance.
一个字符串，指定用于计算的极端点的距离（C）的距离度量的类型。参考如果distance="weuclid"，加权欧氏距离，重量为统计t是1/MAD(t)如果distance="euclid"，欧氏距离;参考。
参数：adj
A character string specifying the type of multiple testing adjustment. <br> If adj="fdr", False Discovery Rate is controled and q values are returned. <br> If adj="adjp", ajusted p values that controls family wise type I error rate are returned.
一个字符串指定多个测试调整的类型。如果adj="fdr"，虚假的发现率，程控和q值返回的参考。 <br>如果adj="adjp"，ajustedp家庭明智的I型错误率值控制返回。
参数：nsig
If adj = "fdr", nsig specifies the number of top differentially expressed genes whose q values will be calculated; we recommend setting nsig < m, as the computation of q values will be extensive. q values for the rest of genes will be approximated to 1. If adj = "adjp", the calculation of the adjusted p values will be for the whole dataset.
如果adj = "fdr"，nsig指定了上面的数字差异表达基因的q值将被计算;我们建议设置nsig < m，q值的计算将是广泛的。 q其余的基因值将接近1。如果adj = "adjp"，调整p值的计算将整个数据集。
参数：quick
A logical variable specifying if a quick but memory requiring procedure will be selected. If quick=TRUE, permutation will be carried out once and stored in memory; If quick=FALSE a fixed seeded sampling procedure will be employed, which requires more computation time as the permutation will be carried out twice, but will not use extra memory for storage.
如果要求快，但是内存的过程中指定一个逻辑变量将被选中。如果quick=TRUE，置换将进行一次，并存储在内存中，如果quick=FALSE将受雇于一个固定的种子抽样程序，这就需要更多的计算时间，置换将分两次进行，但不会用于存储额外的内存。
Details
详情----------Details----------
deds.stat.linkC summarizes multiple statistical measures for the evidence of DE. The DEDS methodology treats each gene as a point corresponding to a gene's vector of DE measures. An "extreme origin" is defined as the maxima of all statistics and the distance from all points to the extreme is computed and ranking of a gene for DE is determined by the closeness of the gene to the extreme. To determine a cutoff for declaration of DE, null referent distributions are generated by permuting the data matrix.
deds.stat.linkC总结DE的证据多元统计的措施。 DEDS的方法对待每一个基因的一个点对应一个基因的向量DE的措施。一个“极端的起源”被定义为所有统计数据的最大值，并从所有点到了极点的距离计算为DE基因的排名是由基因发挥到了极致的亲密确定。要确定一个申报豁免的截止，空指涉分布产生置换的数据矩阵。
Statistical measures currently in the DEDS package include t statistics (tests="t"), fold changes (tests="fc"), F statistics (tests="f"), SAM (tests="sam"), moderated t (tests="modt"), moderated F statistics (tests="modf"), and B statistics (tests="B"). The function deds.stat.linkC interfaces to C functions for the tests and the computation of DEDS. For more flexibility, the user can also use deds.stat which has the same functionality as deds.stat.linkC but is written completely in R (therefore slower) and the user can supply their own function for a statistic not covered in the DEDS package.
统计，目前在DEDS的包的措施，包括t统计量（tests="t"），倍数变化（tests="fc"），F统计量（tests="f"），SAM（tests="sam"），主持ţ（ tests="modt"），主持F统计量（tests="modf"）和B统计（tests="B"）。功能deds.stat.linkC DEDS的测试和计算的C函数接口。更多的灵活性，用户还可以使用deds.stat具有相同的功能deds.stat.linkC但完全写在R（因此速度较慢），用户可以提供自己的功能，不包括在统计DEDS的包。
DEDS can also summarize p values from different statistical models, see deds.pval.
也可以从不同的统计模型总结DEDS的p值，看到deds.pval。
值----------Value----------
An object of class DEDS. See DEDS-class.
对象类DEDS。看到DEDS-class。
作者（S）----------Author(s)----------
Yuanyuan Xiao, <a href="mailto:yxiao@itsa.ucsf.edu">yxiao@itsa.ucsf.edu</a>, <br>
Jean Yee Hwa Yang, <a href="mailto:jean@biostat.ucsf.edu">jean@biostat.ucsf.edu</a>.
参考文献----------References----------
genes from microarray experiment by sets of statistics. Bioinformatics 2005 21:1084-1093.
参见----------See Also----------
deds.pval, deds.stat.
deds.pval，deds.stat。
举例----------Examples----------
X <- matrix(rnorm(1000,0,0.5), nc=10)
L <- rep(0:1,c(5,5))
# genes 1-10 are differentially expressed[差异表达基因的1-10]
X[1:10,6:10]<-X[1:10,6:10]+1
# DEDS summarizing t, fc and sam[DEDS的总结T，FC和sam]
d <- deds.stat.linkC(X, L, B=200)
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。
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发表于 2012-2-25 16:22:58
