lpeAdj(LPEadj)
lpeAdj()所属R语言包:LPEadj
High level lpeAdj function that executes the adjusted local pooled error significance test. If more control over parameters is needed then see documentation for calculateLpeAdj.
高的水平lpeAdj功能,执行调整后的地方汇集误差显着性检验。如果需要更多控制参数,然后看到文档为calculateLpeAdj。
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Applies the LPE algorithm with two additional options. The first is that the original LPE method sets all variances below the max variance in the ordered distribution of variances to the maximum variance. in LPEadj this option is turned off by default. The second option is to use a variance adjustment based on sample size rather than pi/2. By default the LPEadj uses the sample size based variance adjustment. It is recommended to keep both of these options to the default.
适用两个附加选项的液相外延算法。首先是原来的液相外延法设置以下的有序分布差异最大方差最大方差方差。在LPEadj此选项默认关闭。第二种选择是使用基于样本大小,而不是pi / 2的方差调整。默认情况下,LPEadj使用基于方差调整样本大小。建议保留这两个选项的默认。
用法----------Usage----------
lpeAdj(dat, labels=NULL, doMax=FALSE, doAdj=TRUE, q=.01)
参数----------Arguments----------
参数:dat
Replicated data of experiment containing two groups (as matrix or data-frame) </table>
复制的实验数据,包含两组(矩阵或数据框)</ TABLE>
参数:labels
vector of group labels that correspond to the columns of dat. eg. labels=c(0,0,0,1,1,1) describes two groups with three replicates each </table>
向量组标签,对应DAT列。例如。标签= C(0,0,0,1,1,1),描述了三个两组复制每个</ TABLE>
参数:doMax
boolean: if T then all variances below the max variance in the ordered distribution of variances are set to the maximum variance. It is recommended to use the default value of False. </table>
布尔值:如果T,则以下的有序分布的差异最大方差方差设置的最大差异。建议使用默认值false。 </ TABLE>
参数:doAdj
If T then run LPE with using variance adjustment value based on number of replicates (hardcoded in adjValues) rather than pi/2. </table>
如果T然后运行使用数量(硬编码在adjValues)的复制,而不是pi / 2的基础上的差异调整值的液相外延。 </ TABLE>
参数:q
is the quantile width; q=0.01 corresponds to 100 quantiles i.e. percentiles. Bins/quantiles have equal number of genes and are split according to the average intensity A.
位数的宽度; Q = 0.01对应100位数,即百分。箱/位数有同等数量的基因,并根据平均强度A.分裂
Details
详情----------Details----------
The LPE test statistic numerator is the difference in medians between the two experimental conditions. The test statistic denominator is the combined pooled standard error for the two experimental conditions obtained by looking up the var.M from each baseOlig.error variance function. The conversion to p-values is based on the Gaussian distribution for difference if order statistics (medians).
液相外延的检验统计量的分子是在两者之间的实验条件下的中位数的差异。检验统计量的分母是合并汇集寻找var.M从每个baseOlig.error方差函数得到的两个实验条件的标准错误。 p值的转换是基于高斯分布的差异,如果次序统计量(中位数)。
值----------Value----------
Data frame including x, median of x, y, median of y, median difference of (x,y), pooled standard deviation of difference, LPE p-value, outlier flag, probability of an outlier within x or y, .
包括x的中位数,X,Y,y的中位数,中位数差异(X,Y),汇集差异的标准偏差,液相p值,离群标志,离群内X或Y的概率,数据框。
作者(S)----------Author(s)----------
Carl Murie <a href="mailto:carl.murie@mcgill.ca">carl.murie@mcgill.ca</a>,
Nitin Jain <a href="mailto:nitin.jain@pfizer.com">nitin.jain@pfizer.com</a>
参考文献----------References----------
differentially expressed genes with a small number of replicated microarrays, Bioinformatics, 1945-1951.
举例----------Examples----------
# Creating a null dataset (two groups with three[创建一个空的数据集(两组与三]
# replicates each)[复制)]
dat <- matrix(rnorm(6000), ncol=6)
# Applying LPE[应用液相外延]
lpe.result <- lpeAdj(dat, labels=c(0,0,0,1,1,1))
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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