plot.corr.sample(maCorrPlot)
plot.corr.sample()所属R语言包：maCorrPlot
Plot correlation of random pairs of genes
图相关的基因随机对
译者：生物统计家园网 机器人LoveR
描述----------Description----------
plot.corr.sample provides the main functionality of package maCorrPlot: it plots the correlation of random pairs of genes against their variability. Systematic deviations of the plot from a constant zero indicate lack of normalization of the underlying expression matrix.
plot.corr.sample包maCorrPlot提供的主要功能：对随机对相关的基因，其变异图。图的系统偏差，从一个恒定的零表明缺乏底层表达矩阵标准化。
Formally, plot.corr.sample is the plotting method for objects of class corr.sample generated by CorrSample.
正式，plot.corr.sample是corr.sampleCorrSample生成类对象的绘制方法。
panel.corr.sample is the panel function that does the actual plotting work.
panel.corr.sample是面板的功能，实际的绘制工作。
用法----------Usage----------
plot.corr.sample(x, ..., cond, groups, grid = TRUE, refline = TRUE, xlog = TRUE,
scatter = FALSE, curve = FALSE, ci = TRUE, nint = 10,
alpha=0.95, length = 0.1, xlab="Standard Deviation")
panel.corr.sample(x, y, grid = TRUE, refline = TRUE, xlog = TRUE,
scatter = FALSE, curve = FALSE, ci = TRUE, nint = 10,
alpha=0.95, length = 0.1, col.line, col.symbol, ...)
参数----------Arguments----------
参数：x, y
for plot.corr.sample, x is an object of class corr.sample, generated by function CorrSample that contains the pre-computed correlations and standard deviations for the random pairs of genes; for panel.corr.sample, x and y are the x- and y-components (or standard deviation and correlation) of the pairs of genes to be plotted in a specific panel.
plot.corr.sample，x是一个类的对象corr.sample，所产生的功能CorrSample包含预先计算的相关基因的随机双和标准偏差; panel.corr.sample，x和y的x和y组件（或标准差和相关）基因对被绘制在一个特定的面板。
参数：...
either more objects of class corr.sample or plotting arguments passed to the underlying xyplot.
或者更多类对象corr.sample或策划传递底层xyplot的参数。
参数：cond
either a vector or a list of vectors describing multiple objects of class corr.sample; ignored if only one such object (x) is specified. See Details and Examples.
一个向量或描述类的多个对象的向量列表corr.sample;忽略，如果指定一个唯一的对象（x）。细节和例子。
参数：groups
a vector or a list of vectors giving group membership for the random pairs of genes in the corr.sample objects to be plotted, resulting in multiple overlayed plots for each object. See Details and Examples.
绘制一个向量或随机对corr.sample对象的基因组的成员给予的向量名单，在每个对象的多个叠加图。细节和例子。
参数：grid
logical value indicating whether to draw a reference grid
逻辑值，该值指示是否提请参考网格
参数：refline
logical value indicaitng whether to draw a horizontal reference line a zero.
逻辑值indicaitng是否绘制水平参考线零。
参数：xlog
logical value indicating whether to use log-scale on the horizontal axis.
逻辑值，该值指示是否使用横轴上的log规模。
参数：scatter
logical value indicaitng whether the plot the individual pairwise correlations.
是否图indicaitng个别成对相关的逻辑值。
参数：curve
logical value indicating whether to fit a simple model for lack of fit to the correlations.
逻辑值指示是否适合缺乏适宜的相关性的一个简单的模型。
参数：ci
logical value indicating whether to add confidence intervals.
逻辑值指示是否添加置信区间。
参数：nint
number of intervals into which to divide the horizontal axis for calculating average correlations.
到其中横轴划分为计算平均相关间隔数。
参数：alpha
the level of confidence to be plotted.
要绘制的信心水平。
参数：length
the length of the horizontal ticks indicating the ends of the confidence intervals (in inches).
表示置信区间的两端（英寸）水平刻度的长度。
参数：xlab
the label for the horizontal axis.
横轴标签。
参数：col.line, col.symbol
graphical parameters that control the color of the correlation lines and the scatter plotting symbols
控制相关线的颜色和分散绘制符号的图形参数
Details
详情----------Details----------
The underlying plotting engine is xyplot, using panel.corr.sample as panel function, which also interprets most of the graphical parameters. Note that two kinds of arguments can be specified via ...: First, an unlimited number of extra corr.sample objects, in case we want to display different expression measures for the same expression matrix, or compare different expression matrices, or both; this is somewhat similar to the behaviour of boxplot.default. Second, everything that does not inherit from corr.sample is passed on to xyplot, so in theory, the full range of lattice control options is available, as long as they do not conflixt with named arguments to plot.corr.sample, like xlog or xlab.
底层的绘图引擎xyplot用panel.corr.sample面板功能，这也解释了大部分的图形参数。注意两种参数可以指定通过...：首先，一个额外的corr.sample对象的数量不受限制的情况下，我们要显示不同的表达了相同的表达矩阵措施，或比较不同的表达矩阵，或两者兼而有之，这是有点类似boxplot.default的行为。第二，一切不继承corr.sample传递xyplot，所以在理论上，全方位晶格的控制选项是可用的，只要他们不conflixt命名参数plot.corr.sample，xlog或xlab一样。
Two mechanisms for comparisons within the same plot are available: First, as mentioned above, multiple corr.sample objects can be shown in the same graph, each within its own panel. If no cond is specified, these panels are just numbered in the order in which the objects appear in the arguments. Alternatively, one or two factors can be associated with each factor: in the first case, cond is just a vector with as many entries as corr.sample objects in the argument list; these entries are used to label the panels of the corresponding corr.sample objects. In the second case, cond is a list with two such vectors, and the objects are cross-classified according to both categories, and the panels are arranged in a row-column pattern reflecting this cross-classification, see Examples.
两个机制为同一小区内的比较是：首先，如上所述，多个corr.sample对象可以在相同的图形，每一个在自己的面板显示。如果没有cond指定，这些小组只是在对象中的参数出现的顺序编号。另外，一个或两个因素，可以与各因素：在第一种情况下，cond只是向量corr.sample在参数列表中的对象与尽可能多的条目，这些条目用来标记面板相应的corr.sample对象。在第二种情况下，cond是有两个这样的向量列表，并根据两类的对象是交叉分类，和面板安排在一排列反映这一交叉分类的模式，看到的例子。
The other mechanism for graphical comparisons within the same plot is via groups, which draws different correlation curves for different sub-groups of pairs of genes; the standard example is to classify pairs of genes according to their common or average score in regard to a quality control measure like the MAS5 presence calls, see Examples. These sub-groups are specified via groups; if there is only one corr.sample object in the function call (x), groups is just a vector with as many entries as there are random paris of genes in x. If several objects of class corr.sample have been specified in the function call, groups is a list of as many vectors as objects, where each vector has as many entries as the corresponding object has pairs of genes.
groups，吸引不同子对基因组的不同的相关曲线图形比较在同一小区的其他机制是通过标准的例子是对基因分类，根据他们共同的或平均得分把像MAS5存在通话质量控制措施，看到的例子。这些分组通过groups;如果有只有一个corr.sample在函数调用对象（x）groups只是一个向量与尽可能多的条目指定有x随机基因巴黎。如果几个对象类corr.sample已在函数调用中指定的，groups是许多向量作为对象，其中每个向量相应的对象有许多条目对基因的列表。
值----------Value----------
A plot created by xyplot.
xyplot创建一个图。
警告----------Warning ----------
cond is translated into conditioning variables for xyplot, which will not hesitate to average correlations across different corr.sample objects. It's hard to see when this would be a good idea, therefore plot.corr.sample will generate a warning.
condxyplot，它会毫不犹豫地跨不同corr.sample对象的平均相关的调节变量被翻译成。很难看到时，这将是一个好主意，因此plot.corr.sample将产生一个警告。
作者（S）----------Author(s)----------
Alexander Ploner <a href="mailto:Alexander.Ploner@ki.se">Alexander.Ploner@ki.se</a>
参考文献----------References----------
http://www.pubmedcentral.gov/articlerender.fcgi?tool=pubmed&pubmedid=15799785
参见----------See Also----------
CorrSample, xyplot
CorrSample，xyplot
举例----------Examples----------
# Get small example data[小示例数据]
data(oligodata)
dim(datA.rma)
dim(datB.rma)
# Compute the correlations for 500 random pairs, [计算随机对500的相关性，]
# Larger numbers are reasonable for larger data sets[更大的数字更大的数据集合理]
cs1.rma = CorrSample(datA.rma, 500, seed=210)
plot(cs1.rma)
# Change the plot[改变图]
plot(cs1.rma, scatter=TRUE, curve=TRUE, alpha=0.99)
# Compare with MAS5 values for the same data set[比较MAS5值相同的数据集]
cs1.mas5 = CorrSample(datA.mas5, 500, seed=210)
plot(cs1.rma, cs1.mas5, cond=c("RMA","MAS5"))
# We group pairs of gene by their average number of MAS5 present calls[我们的基因组对他们的MAS5目前呼叫的平均数]
pcntA = rowSums(datA.amp[cs1.mas5$ndx1, ]=="P") +
rowSums(datA.amp[cs1.mas5$ndx2, ]=="P")
hist(pcntA)
pgrpA = cut(pcntA, c(0, 20, 40, 60), include.lowest=TRUE)
table(pgrpA)
# Plot the RMA values according to their MAS5 status [根据他们的MAS5状态绘制的RMA值]
# The artificial correlation is due to gene pairs with few present calls[人工的相关性是由于基因对几本检测]
plot(cs1.rma, groups=pgrpA, nint=5, auto.key=TRUE, ylim=c(-0.3, 0.5))
# Combine grouping and multiple conditions[结合分组和多个条件]
plot(cs1.rma, cs1.mas5, cond=c("RMA","MAS5"), groups=list(pgrpA, pgrpA),
nint=5, auto.key=TRUE, ylim=c(-0.3, 0.5))
# Compare with second data set[第二个数据集比较]
# Specify more than one condition[指定一个以上的条件]
cs2.rma = CorrSample(datB.rma, 500, seed=391)
cs2.mas5 = CorrSample(datB.mas5, 500, seed=391)
plot(cs1.rma, cs1.mas5, cs2.rma, cs2.mas5,
cond=list(c("RMA","MAS5","RMA","MAS5"), c("A","A","B","B")))
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。
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发表于 2012-2-25 23:59:39
