dyebias.monotonicityplot(dyebias)
dyebias.monotonicityplot()所属R语言包：dyebias
Show the degree of monotonicity of the dye bias across the slides. DEPRACATED
显示的单调的跨越幻灯片染料偏见的程度。 DEPRACATED
译者：生物统计家园网 机器人LoveR
描述----------Description----------
If you order genes by their iGSDB, and hybridizations by slide bias, the graphs of each gene should form a 'fan' out of the origin (see also dyebias.trendplot). This function plots the regression slope of each gene, ordered by iGSDB and slide bias. If the uncorrected total dye bias is indeed monotonous, an increasing trend should be visible.
如果他们iGSDB和按幻灯片偏差杂交秩序基因，每个基因的图应该形成一个出的起源“风扇”（也dyebias.trendplot）的。这个函数绘制每一个基因的回归斜率下令，由iGSDB和幻灯片偏见。如果裸染料偏见实在是单调，增加的趋势应该是可见的。
This function has been depracated, as it is of limited use and takes too long to compute.
此功能已depracated，因为它是有限的使用和计算时间过长。
用法----------Usage----------
dyebias.monotonicityplot(data,
iGSDBs,
dyebias.percentile = 5,
order = NULL,
output = NULL,
pch = 19, cex = 0.3, cex.lab = 1.4,
ylim = c(-0.2, 0.2),
xlab = "rank", ylab = "slope",
sub = NULL,
...)
参数----------Arguments----------
参数：data
The marrayNorm to determine the degree of monotonicity for
marrayNorm来确定单调程度
参数：iGSDBs
A data frame with intrinsic gene-specific dye biases, the same as that used in dyebias.apply.correction, probably returned by <br> dyebias.estimate.iGSDBs; see there for documentation.
可能具有内在的特定基因的染料偏见，在dyebias.apply.correction使用相同的数据框，返回参考dyebias.estimate.iGSDBs;看到那里的文档。
参数：dyebias.percentile
The percentile of intrinsic gene specific dye biases (iGSDBs) for which to highlight the reporters. Default should suffice in almost all cases.
内在基因特定的染料偏见（iGSDBs）突出记者的百分位。默认情况下应该足以在几乎所有情况下。
参数：order
If order==NULL, the slides are sorted by increasing slide bias prior to boxplotting. This is typically done for data that is not yet dye bias corrected. (This order is also returned in the object returned). If order!=NULL, the slides are put into this order first. This is typically done for a dye bias-corrected data set, using the order of the uncorrected set.
如果order==NULL，幻灯片进行排序，增加幻灯片偏见到boxplotting前。这通常是尚未染料偏差纠正的数据。 （这个顺序在返回的对象返回）。如果order!=NULL，幻灯片投入这个顺序第一。这通常是染料偏置校正数据集，使用裸集秩序。
参数：output
Specifies the output. If NULL, the existing output device is used; if output is one of "X11", "windows", "quartz", a new X11 (Unix)/windows (Windows)/quartz (Mac) device is created. If output is a string ending in one of ".pdf", ".png", ".eps", ".ps" is given, a file of that name and type is created and closed afterwards.
指定输出。如果NULL，现有输出设备的使用; output如果是"X11", "windows", "quartz"，一个新的X11（UNIX）/ /石英窗口（Windows）中（MAC）设备创建一个。 output如果是一个字符串“".pdf", ".png", ".eps", ".ps"给出一个文件，名称和类型的创建和关闭后结束。
参数：pch, cex, cex.lab, ylim, xlab, ylab
As for plot()
plot()
参数：sub
The subtitle. If sub==NULL, a string giving the tau and p-value of the Mann-Kendall test is used; otherwise as for plot()
字幕。如果sub==NULL，给头和Mann-Kendall检验的p值是一个字符串;否则plot()
参数：...
Other arguments are passed on to plot()
其他的参数被传递plot()
Details
详情----------Details----------
The total dye bias appears to be the product of iGSDB and slide bias. In other words, it is monotonous (always increasing or always decreasing), both with respect to the intrinsic gene specific dye bias and with respect to the slide bias. This function orders genes by their iGSDB and the slides by slide bias. Subsequently a linear regression of each gene is done, with x being the slide bias rank (not the slide bias itself), and y being the M. The slopes of each linear regression line should be an increasing array of values, representing the 'fan' of lines. The array of slopes is plotted (versus the rank). Generally, a clear trend is visible for uncorrected hybridizations, and the trend has disappeared after dye bias correction.
总的染料偏见，似乎是的iGSDB和幻灯片偏见的产物。换句话说，它是单调（总是增加或总是下降），两个方面的内在基因特定的染料偏见和尊重幻灯片偏见。此功能令幻灯片偏见，他们iGSDB和幻灯片的基因。随后的每一个基因的线性回归，x是幻灯片偏见排名（幻灯片偏见本身），和y是研究每个线性回归线的斜率应该增加值的数组，表示“粉丝的“行。绘制一系列的斜坡（与排名）。一般来说，一个明显的趋势是可见裸杂交，而且染料偏差修正后消失的趋势。
值----------Value----------
The order of the slide bias is returned, for use in plotting the behaviour of the regression slopes in the corrected data set.
返回幻灯片偏见秩序，绘制校正数据集的回归斜坡的行为。
注意----------Note----------
This function takes very long to compute, since it calculates regressions for each gene.
此功能需要很长的时间来计算，因为它计算每个基因的回归。
作者（S）----------Author(s)----------
Philip Lijnzaad <a href="mailto:p.lijnzaad@umcutrecht.nl">p.lijnzaad@umcutrecht.nl</a>
参考文献----------References----------
Kemmeren, P., van Hooff, S.R and Holstege, F.C.P. (2009). Adaptable gene-specific dye bias correction for two-channel DNA microarrays. Molecular Systems Biology, 5:266, 2009. doi: 10.1038/msb.2009.21.
参见----------See Also----------
dyebias.monotonicity, dyebias.trendplot
dyebias.monotonicity，dyebias.trendplot
举例----------Examples----------
## Not run: [＃无法运行：]
options(stringsAsFactors = FALSE)
library(dyebias)
library(dyebiasexamples)
data(data.raw)
data(data.norm)
### obtain estimate for the iGSDBs:[＃获得的iGSDBs的估计：]
iGSDBs.estimated <- dyebias.estimate.iGSDBs(data.norm,
is.balanced=TRUE,
verbose=FALSE)
### choose the estimators and which spots to correct:[＃选择的估计和景点，以纠正：]
estimator.subset <- dyebias.umcu.proper.estimators(maInfo(maGnames(data.norm)))
application.subset <- maW(data.norm) == 1 &
dyebias.application.subset(data.raw=data.raw, use.background=TRUE)
### do the correction:[＃做更正：]
correction <- dyebias.apply.correction(data.norm=data.norm,
iGSDBs = iGSDBs.estimated,
estimator.subset=estimator.subset,
application.subset = application.subset,
verbose=FALSE)
layout(matrix(1:2, nrow=1,ncol=2))
order <- dyebias.monotonicityplot(data=data.norm,
iGSDBs=iGSDBs.estimated, # from e.g. dyebias.estimate.iGSDBs[从如dyebias.estimate.iGSDBs]
order=NULL, # i.e., order by increasing slide bias[即，为了增加幻灯片偏见]
output=NULL,
main="before correction"
)
order <- dyebias.monotonicityplot(data=correction$data.corrected,
iGSDBs=iGSDBs.estimated,
order=order, # order by the original slide bias[整理原始幻灯片偏见]
output=NULL,
main="after correction"
)
## 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 16:50:04
