differential.probs(joda)
differential.probs()所属R语言包：joda
Calculating probabilities of differential expression in perturbation experiments
差异表达的概率计算扰动实验
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Returns probabilities of differential expression for genes under perturbation of a set of regulators. Takes as input perturbation data and beliefs about known genes.
一套监管机构的扰动下返回基因的差异表达的可能性。作为输入扰动数据和有关已知基因的信念。
用法----------Usage----------
differential.probs(data, beliefs, verbose, plot.it)
参数----------Arguments----------
参数：data
A matrix of log expression ratios perrturbation vs control, for the genes (rows), in the perturbations of the regulators (columns). The data has to have row and colnames specified by the user.
（行）的基因，在监管机构（列）的扰动，矩阵的log表达率perrturbation与对照。数据必须具有由用户指定的行和colnames。
参数：beliefs
A list with names being a subset of the regulators (i.e., the names of beliefs have to be a subset of the columns of the data). Each list entry for a given regulator is a matrix with rows corresponding to the genes that are known to respond in some way to the perturbation of this regulator. The rownames of the matrix must be a subset of the rows in the data. The matrix can have either two or three columns. Each row is a distribution over the differential and unchanged cluster (2 columns) or over down, up-regulated and unchanged cluster of genes (3 columns). This distribution reflects the certainties with which a gene that corresponds to this row belongs to each of those clusters.
一个被监管的一个子集名称的列表（即名称beliefs是一个data列的子集）。每一个给定的稳压器的列表项是矩阵的行对应已知的基因在一些扰动这种调节的方式回应。矩阵rownames，必须是data行的一个子集。矩阵可以有两个或三个列。每一行是一个分布在差不变聚类（2列）或以上的下降，上调不变的基因簇（3列）。这种分布反映了确定性，其中一个基因对应此行属于每个聚类。
参数：verbose
When TRUE, for each regulator and its perturbation data, the execution prints out the parameters of the fitted model(s), indicating which components are differential and which are unchanged.
当为true时，每个稳压器及其扰动数据，执行打印出的拟合模型（S）的参数，说明哪些组件是差的，哪些是不变的。
参数：plot.it
When TRUE, for each regulator and its perturbation data, the execution plots the Gaussian components of the fitted model(s), indicating which components are differential and which are unchanged.
如果为TRUE，每个稳压器及其扰动数据，执行图高斯拟合模型（S）的组成部分，说明哪些组件是差的，哪些是不变的。
Details
详情----------Details----------
For each regulator, a belief-based mixture model is fitted to the observations in the data. The fitted models have the number of model components equal to the number of columns in the corresponding beliefs. If no beliefs are given, unsupervised two-component mixture modeling is applied.
每个稳压器，一个信念为基础的混合模型拟合意见data。拟合模型的模型组件的数量等于数列在相应的信念。如果没有信仰，无人看管应用于双组分混合模型。
值----------Value----------
A matrix with columns for the regulators, rows for the genes, and entries giving the signed probabilities of differential expression.
与监管机构，一排排的基因，并给予差异表达的签署概率条目列的矩阵。
作者（S）----------Author(s)----------
Ewa Szczurek
参考文献----------References----------
参见----------See Also----------
regulation.scores, deregulation.scores
regulation.scores，deregulation.scores
举例----------Examples----------
data(damage)
# Get the probabilities of differential expression[获取差异表达的概率]
# for the knockout of p53 in healthy cells[在健康单元中的p53淘汰赛]
probs.healthy.p53= differential.probs(data.healthy[,"p53",FALSE],
beliefs.healthy["p53"], TRUE,TRUE)
# Get the probabilities of differential expression[获取差异表达的概率]
# for the knockout of Ste12 under pheromone treatment [信息素的治疗下，Ste12淘汰赛]
library(bgmm)
data(Ste12)
data=as.matrix(Ste12Data)
colnames(data)="Ste12"
beliefs=list(Ste12=Ste12Beliefs)
diff.p=differential.probs(data,beliefs,TRUE,TRUE)
## Not run: [＃无法运行：]
probs.healthy= differential.probs(data.healthy, beliefs.healthy, TRUE,TRUE)
## 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 2012-2-25 22:48:11
