sim.refDesign(snm)
sim.refDesign()所属R语言包：snm
Simulates data from a two-color microarray experiment using a reference design.
从两色的芯片使用的参考设计的实验模拟数据。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Simulates a two channel experiment with a reference design. Used as an example for snm function call.
模拟与参考设计的双通道实验。作为SNM函数调用的一个例子。
用法----------Usage----------
sim.refDesign(seed)
参数----------Arguments----------
参数：seed
Numeric value used to seed random number generator.
用于种子随机数发生器的数值。
Details
详情----------Details----------
Simulated data set influenced by a probe-specific biological variable, and intensity-dependent array and dye effects. Data were simulated assuming a uniform reference design for a total of 25,000 probes and 20 arrays, each consisting of two channels. The reference channel consists of a single reference RNA population. The experimental channel measures a dichotomous biological variable specifying two groups (Group 1 and Group 2), with 10 samples per group. The baseline probe intensities were sampled from a chi(1,2) distribution. Any baseline intensities greater than 15 were set to a random value from the interval [15,16]. The random variation terms were sampled from a Normal(0,0.25) and the array and dye functions were defined by randomly sampling coefficients for a two-dimensional B-spline basis functions from a Normal(0,1).
模拟数据集探针特定的生物变量的影响，并依赖强度的阵列和染料的影响。数据模拟假设共有25000探针和20阵列，每两个通道组成一个统一的参考设计。参考通道由一个单一的参考RNA的人口。实验通道测量生物二分法变量指定两组（第1组和2组），每10组样品。从智（1,2）分布进行抽样基线探针强度。任何基线强度大于15设置一个随机值从区间[15,16]。从正常（0,0.25）随机变化的条款进行抽样和随机抽样为一个二维的B样条基函数从一个正常的（0,1）的系数被定义数组和染料功能。
A randomly selected subset of 30% of the probes was defined as influenced by the biological group variable. The magnitude of the biological effects were sampled from a Normal(1,0.3) distribution. An instance of this simulated data can be generated using the code in the examples section below.
30％的探针随机选择的一个子集被定义为生物组变量的影响。从一个正常的分布（1,0.3）的生物效应的大小进行抽样。此模拟数据的一个实例可以生成下面的示例一节中使用的代码。
值----------Value----------
参数：<code>raw.data</code>
a 25,000 by 50 matrix of simulated data generated according to the description above.
根据上面的描述矩阵生成的模拟数据25,000 50。
参数：<code>true.nulls</code>
a vector of indices corresponding to the rows in raw.data of the probes unaffected by the biological variable of interest
指数相应利益的生物变量探针不受影响raw.data行向量
参数：<code>bio.var</code>
a model matrix of the biological variable of interest.
对生物的兴趣变量的模型矩阵。
参数：<code>adj.var</code>
a model matrix of the probe-specific adjustment variables. In this case set to NULL.
一个探针的具体调整变量的模型矩阵。在这种情况下设置为NULL。
参数：<code>int.var</code>
a data frame of the intensity-dependent adjustment variables
一个数据框依赖强度调整变量
作者（S）----------Author(s)----------
Brig Mecham <brig.mecham@sagebase.org> and John D. Storey <jstorey@princeton.edu>
参见----------See Also----------
snm, sim.singleChannel, sim.doubleChannel, sim.preProcessed
snm，sim.singleChannel，sim.doubleChannel，sim.preProcessed
举例----------Examples----------
## Not run: [＃无法运行：]
# reference design on channel level data[通道级别的数据上的参考设计]
# reference channel is included in bio.var[参考通道包括在bio.var]
refChannel <- sim.refDesign(12347)
snm.obj <- snm(refChannel$raw.data,refChannel$bio.var, refChannel$adj.var, refChannel$int.var)
ks.test(snm.obj$pval[refChannel$true.nulls],"punif")
# reference design on log ratio data[log比数据上的参考设计]
refChannel <- sim.refDesign(12347)
refChannel$raw.data = refChannel$raw.data[,1:20]-refChannel$raw.data[,21:40]
# removing reference channel variables[消除参考通道变量]
refChannel$bio.var = refChannel$bio.var[1:20,-3]
refChannel$int.var = data.frame(refChannel$int.var[1:20,1])
snm.obj <- snm(refChannel$raw.data,refChannel$bio.var, refChannel$adj.var, refChannel$int.var)
ks.test(snm.obj$pval[refChannel$true.nulls],"punif")
## End(Not run)[＃结束（不运行）]
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 2012-2-26 14:37:37
