pumaDE(puma)
pumaDE()所属R语言包：puma
Calculate differential expression between conditions
计算条件之间的差异表达
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function generates lists of genes ranked by probability of differential expression (DE). This uses the PPLR method.
该函数生成的基因差异表达（DE）的概率排名名单。这使用PPLR方法。
用法----------Usage----------
pumaDE(
eset
, design.matrix = createDesignMatrix(eset)
, contrast.matrix = createContrastMatrix(eset)
)
参数----------Arguments----------
参数：eset
An object of class ExpressionSet.
对象类ExpressionSet。
参数：design.matrix
A design matrix
一个设计矩阵
参数：contrast.matrix
A contrast matrix
对比矩阵
Details
详情----------Details----------
A separate list of genes will be created for each contrast of interest.
将创建一个单独的基因列表为每个感兴趣的对比。
Note that this class returns a DEResult-class object. This object contains information on both the PPLR statistic values (which should generally be used to rank genes for differential expression), as well as fold change values (which are generally not recommended for ranking genes, but which might be useful, for example, to use as a filter). To understand more about the object returned see DEResult-class, noting that when created a DEResult object with the pumaDE function, the statistic method should be used to return PPLR values. Also note that the pLikeValues method can be used on the returned object to create values which can more readily be compared with p-values returned by other methods such as variants of t-tests (limma, etc.).
请注意，这个类返回一个DEResult-class对象。 PPLR统计值（一般应使用排名差异表达的基因），以及褶皱的变化值（一般不推荐排名基因，但它可能是有用的，例如，这个对象包含的信息作为一个过滤器的使用）。要了解更多有关对象返回DEResult-class，指出创建用的pumaDE功能DEResult对象时，应statistic方法用于返回PPLR值。还注意到，pLikeValues方法可以用来创建可以更容易地与其他方法，如t-检验（limma等）的变种产生的P-值相比的值返回的对象。
While it is possible to run this function on data from individual arrays, it is generally recommended that this function is run on the output of the function pumaComb (which combines information from replicates).
虽然这是可能的数据从单个阵列上运行此功能，所以一般建议，这个功能是运行函数的输出pumaComb（结合从复制的信息）。
值----------Value----------
An object of class DEResult-class.
对象类DEResult-class。
作者（S）----------Author(s)----------
Richard D. Pearson
参见----------See Also----------
Related methods calculateLimma, calculateFC, calculateTtest, pumaComb, pumaCombImproved, mmgmos, pplr, createDesignMatrix and createContrastMatrix
相关方法calculateLimma，calculateFC，calculateTtest，pumaComb，pumaCombImproved，mmgmos，pplr，createDesignMatrix“ createContrastMatrix
举例----------Examples----------
# Next 4 lines commented out to save time in package checks, and saved version used[接下来的4行注释掉包检查，以节省时间，并保存版本使用]
# if (require(affydata)) {[（要求（affydata））{]
# data(Dilution)[数据（稀释）]
# eset_mmgmos <- mmgmos(Dilution)[< - mmgmos eset_mmgmos（稀释）]
# }[}]
data(eset_mmgmos)
# Next line shows that eset_mmgmos has 4 arrays, each of which is a different[下一行显示，eset_mmgmos有4阵列，其中每一个不同]
# condition (the experimental design is a 2x2 factorial, with both liver and[条件（实验设计是一个2x2的因子，肝脏和]
# scanner factors)[扫描器的因素）]
pData(eset_mmgmos)
# Next line shows expression levels of first 3 probe sets[下一行显示，前3个探针组的表达水平]
exprs(eset_mmgmos)[1:3,]
# Next line used so eset_mmgmos only has information about the liver factor[下一行使用，所以eset_mmgmos只有肝因子的信息]
# The scanner factor will thus be ignored, and the two arrays of each level[扫描器的因素将被忽略，每个级别的两个数组]
# of the liver factor will be treated as replicates[肝因子，将被视为重复]
pData(eset_mmgmos) <- pData(eset_mmgmos)[,1,drop=FALSE]
# To save time we'll just use 100 probe sets for the example[为了节省时间，我们只使用100个探针组的例子]
eset_mmgmos_100 <- eset_mmgmos[1:100,]
eset_comb <- pumaComb(eset_mmgmos_100)
eset_combimproved <- pumaCombImproved(eset_mmgmos_100)
pumaDEResults <- pumaDE(eset_comb)
pumaDEResults_improved <- pumaDE(eset_combimproved)
topGeneIDs(pumaDEResults,6) # Gives probeset identifiers[给出probeset标识符]
topGeneIDs(pumaDEResults_improved,6)
topGenes(pumaDEResults,6) # Gives row numbers[给出的行号。]
topGenes(pumaDEResults_improved,6)
statistic(pumaDEResults)[topGenes(pumaDEResults,6),] # PPLR scores of top six genes[PPLR分数前六名的基因]
statistic(pumaDEResults_improved)[topGenes(pumaDEResults_improved,6),]
FC(pumaDEResults)[topGenes(pumaDEResults,6),] # Fold-change of top six genes[倍数前六名的基因变化]
FC(pumaDEResults_improved)[topGenes(pumaDEResults_improved,6),]
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 11:36:30
