MEDME(MEDME)
MEDME()所属R语言包：MEDME
Determining the logistic model of MeDIP enrichment in respect to the expected DNA methylation level
在确定预期的DNA甲基化水平Logistic模型MeDIP富集
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Probe-level MeDIP weighted enrichment is compared to the expected DNA methytlation level. The former is determined applying MeDIP protocol to a fully methylated DNA. The latter is determined as the count of CpGs for each probe. This is assumed to be the methylation level of each probe in a fully methylated sample.
探针级MeDIP加权富集比预期的DNA methytlation水平。前者是确定申请MeDIP协议完全甲基化的DNA。后者则是确定的CPGs为每个探针的计数。这被认为是在一个完全甲基化的样本每个探针的甲基化水平。
用法----------Usage----------
MEDME(data, sample, CGcountThr = 1, figName = NULL)
参数----------Arguments----------
参数：data
An object of class MEDMEset
一个类MEDMEset对象
参数：sample
Integer; the number of the sample to be used to fit the model, based on the order of samples in the smoothed slot
整数;被用来拟合模型的样本数量的基础上样本平滑槽的顺序
参数：CGcountThr
number; the threshold to avoid modelling probes with really low methylation level, i.e. CpG count
数的阈值，以避免与真正的低甲基化水平，即中央人民政府计数建模探针
参数：figName
string; the name of the file reporting the model fitting
字符串文件名报告模型拟合
Details
详情----------Details----------
The model should be applied on calibration data containing MeDIP enrichment of fully methylated DNA, most likely artificially generated (see references). Nevertheless, in case chromosome or genome-wide human tiling arrays are used a regular sample could be used too. In fact, human genomic DNA is known to be hyper-methylated but in the promoter regions. Of course the performance of the method is expected to be somehow affected by this approximation.
该模型应适用于含有MeDIP富集的DNA甲基化，最有可能产生的人为（见参考资料）的校准数据。不过，在情况下染色体或人类全基因组平铺阵列用于定期样本可以使用。事实上，在人类基因组DNA被称为是超甲基化，但在启动子区域。当然，该方法的性能预计可不知何故，此近似的影响。
值----------Value----------
The logistic model as returned from the multdrc function from the drc R library
从刚果（金）R库multdrc函数返回从Logistic模型
参考文献----------References----------
<h3>See Also</h3> <code>smooth</code>, <code>CGcount</code>
举例----------Examples----------
data(testMEDMEset)
## just an example with the first 1000 probes[＃只是一个例子，与1000探针]
testMEDMEset = smooth(data = testMEDMEset[1:1000, ])
library(BSgenome.Hsapiens.UCSC.hg18)
testMEDMEset = CGcount(data = testMEDMEset)
MEDMEmodel = MEDME(data = testMEDMEset, sample = 1, CGcountThr = 1, figName = NULL)
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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 2012-2-26 00:39:24
