plotCtVariation(HTqPCR)
plotCtVariation()所属R语言包:HTqPCR
Plot variation in Ct values across replicates
复制整个图变化值在CT
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Examine the variation in Ct values, either across features present multiple times on each card, or for within different groups of samples. The function supports both a summarised and a more detailed output.
检查Ct值的变化,跨功能提出每张卡多次,或不同群体的样本内。该功能支持,既是一个总结,更详细的输出。
用法----------Usage----------
plotCtVariation(q, cards = TRUE, variation = "var", type = "summary", sample.reps, feature.reps, log = FALSE, add.featurenames = FALSE, ylab, n.col, ...)
参数----------Arguments----------
参数:q
object of class qPCRset.
对象类qPCRset。
参数:cards
vector, the numbers of the cards to plot. Defaults to TRUE = all cards.
向量,卡的数量来绘制。默认为TRUE =所有卡片。
参数:variation
character string indication whether to calculate the variation, "var", or standard deviation, "sd".
字符串指示是否计算的变化,“无功”,或标准差,“SD”。
参数:type
character string indicating whether to output the results in a summarised boxplot, "summary" or as a more detailed scatter plot, "detail". See Details and the examples.
字符串,指示是否在总结盒形图,“摘要”,或作为一个更详细的散点图,“细节”的输出结果。查看详细信息和例子。
参数:sample.reps
a vector grouping the samples (see Details). Overrides feature.reps.
向量的分组样本(见详情)。覆盖feature.reps的。
参数:feature.reps
a vector grouping the features according to which are replicates. Per default featureNames(q) are used.
分组的功能,根据的是矢量复制。每默认的featureNames(q)使用。
参数:log
logical, should the results be converted into log10 values.
逻辑的结果,应该被转换成log10的值。
参数:add.featurenames
logical, if type="detail" should the names of each feature be added to the scatter plot.
逻辑,type="detail"如果每个功能的名字应该被添加到散点图。
参数:ylab
character, the label of the y-axis.
字符,y轴的标签。
参数:n.col
integer, if type="detail" how many columns should the scatterplots be presented in. Defaults to 3, or n.samples(q) if <3.
整数,如果type="detail"多少列散点图呈现英寸默认为3,或n.samples(q)如果<3。
参数:...
further arguments passed to boxplot or plot.
通过进一步的论据boxplot或plot。
Details
详情----------Details----------
It is often useful to examine the data to determine if some samples are inherently more variable than other, or if the concordance between replicates on each qPCR card is acceptable. Using type="summary" generates a boxplot with all the variation values, either across genes (if sample.reps is set) or with each samples (default, or if feature.reps is set). That way the general distribution of variation or standard deviation values can be compared quickly.
检查数据,以确定是否一些样品是天生比其他更多的变数,或者如果重复对每个定量PCR卡之间的一致性是可以接受的,它往往是有益的。使用type="summary"生成一个与所有的变化值的盒形图,无论是整个基因(如sample.reps设置)或每个样品(默认情况下,如果feature.reps设置)。这样的变化或标准偏差值一般分布可以比较迅速。
If it looks like there's an unacceptable (or interesting) difference in teh variation, this can be further investigated using type="detail". This will generate multiple sub-plots, containing a single scatterplot of variation versus mean for each gene (if sample.reps is set) or each sample (default, or if feature.reps is set). Including the mean in the plot can be used to assess heteroskedasticity in the data.
如果它看起来像有一个不可接受的(或有趣)在格兰变化的差异,这可以进一步探讨使用type="detail"。这将产生多个子图,包含一个单一的变化散点图与平均每个基因(sample.reps如果设置)或每个样品(默认情况下,如果feature.reps设置)。包括在图的平均值可以用来评估数据的异方差。
值----------Value----------
A plot is created on the current graphics device. The variation and mean across each type of replicate is returned invisibly in a list with "Var" and "Mean" slots.
当前图形设备上创建一个图。在每个复制型的变化和平均返回列表中的无形“无功”和“中庸”插槽。
作者(S)----------Author(s)----------
Heidi Dvinge
参见----------See Also----------
plotCtReps for cases where the qPCR card only contains two replicates of each feature. plotCVBoxes for other ways of plotting variation within different groups.
plotCtReps每个功能重复的qPCR卡只包含两情况件。 plotCVBoxes图在不同群体的变化等方式。
举例----------Examples----------
# Load some example data[加载一些示例数据]
data(qPCRraw)
# Get a summary of the standard deviation across replicated features[整个复制功能得到标准差摘要]
plotCtVariation(qPCRraw, variation="sd", log=TRUE)
# Summary of the first 40 genes, assuming there are 3 groups of samples[摘要的第一个假设有40个基因,有3组样品]
plotCtVariation(qPCRraw[1:40,], sample.reps=rep(1:2,3))
# Detailed summary of variation versus mean Ct value for replicated features within each sample[详细摘要的变化与平均CT值在每个样品的复制功能]
plotCtVariation(qPCRraw, type="detail", log=TRUE)
plotCtVariation(qPCRraw, type="detail")
# Add feature names to see which the highly varying replicates are. [新增功能的名称,以高度的变复制。]
plotCtVariation(qPCRraw, type="detail", add.featurenames=TRUE, pch=" ", cex=0.8)
# Use different information to indicate which features are replicates[使用不同的信息表明哪些功能复制]
plotCtVariation(qPCRraw, type="detail", feature.reps=paste("test", rep(1:96, each=4)))
# Examine variation across samples for the first 9 features[检查变化跨样本为第9功能]
plotCtVariation(qPCRraw[1:9,], type="detail", sample.reps=paste("mutant", rep(1:3,2)), add.featurenames=TRUE)
# Examine the output[检查输出]
test <- plotCtVariation(qPCRraw, variation="sd")
names(test)
head(test[["Var"]])
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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