rangeGate(flowStats)
rangeGate()所属R语言包：flowStats
Find most likely separation between positive and negative
寻找最有可能的积极和消极之间的分离
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function tries to find a reasonable split point between the two hypothetical cell populations "positive" and "negative".
该函数试图找到合理的分割点之间的“积极”和“负翁”的两个假设的单元群。
用法----------Usage----------
rangeGate(x, stain, alpha="min", sd=2, plot=FALSE, borderQuant=0.1,
absolute=TRUE, filterId="defaultRectangleGate", positive=TRUE,
refLine=NULL, ...)
rangeFilter(stain, alpha="min", sd=2, borderQuant=0.1,
filterId="defaultRangeFilter")
参数----------Arguments----------
参数：x
A flowSet or flowFrame.
一个flowSet或flowFrame。
参数：stain
A character scalar giving the flow parameter for which to compute the separation.
字符标量计算分离的流动参数。
参数：alpha
A tuning parameter that controls the location of the split point between the two populations. This has to be a numeric in the range [0,1], where values closer to 0 will shift the split point closer to the negative population and values closer to 1 will shift towards the positive population. Additionally, the value of alpha can be "min", in which case the split point will be selected as the area of lowest local density between the two populations.
调谐参数控制的两个种群之间的分割点的位置。这已是在范围[0,1]值接近0，其中将转向分割点接近接近1负的人口和价值观将转向积极的人口数字。此外，的alpha价值可以是"min"分割点，在这种情况下，将选择局部密度最低的两个种群之间的区域。
参数：sd
For the case where there is only a single population, the algorithm falls back to esitmating the mode of this population and a robust measure of the variance of it distribution. The sd tuning parameter controls how far away from the mode the split point is set.
那里是只有一个单一的人口的情况下，该算法回落到esitmating这部分人口的模式和它分布的方差稳健的措施。 sd调整参数控制分割点设置模式从离多远。
参数：plot
Create a plot of the results of the computation.
创建一个计算结果的图。
参数：borderQuant
Usualy the instrument is set up in a way that the positive population is somewhere on the high end of the measurement range and the negative population is on the low end. This parameter allows to disregard populations with mean values in the extreme quantiles of the data range. It's value should be in the range [0,1].
扇贝仪器设置的方式，积极的人口是某处测量范围的高端和低端的人口负。此参数可以无视人口数据范围的极端位数的平均值。它的价值应该在范围[0,1]。
参数：absolute
Logical controling whether to classify a population (positive or negative) relative to the theoretical measurment range of the instrument or the actual range of the data. This can be set to TRUE if the alignment of the measurment range is not optimal and the bulk of the data is on one end of the theoretical range.
逻辑温控是否分类理论的测算范围的仪器或数据的实际范围相对人口（正或负）。这可以设置为TRUE如果不是最佳的测算范围内的对齐和理论范围的一端是大量的数据。
参数：filterId
Character, the name assigned to the resulting filter.
字符，分配到由此产生的过滤器的名称。
参数：positive
Create a range gate that includes the positive (TRUE) or the negative (FALSE) population.
创建一个范围，其中包括积极的门（TRUE）或负（FALSE）人口。
参数：refLine
Either NULL or a numeric of lenth 1. If NULL, this parameter is ignored. When it is set to a numeric, the minor sub-population (if any) below this reference line will be igored while determining the separator between positive and negative.
要么NULL或数字全长1。如果NULL，则忽略此参数。被设置为一个数字，未成年子人口（如有），低于该参考线将确定正负极之间的隔膜，而igored当它。
参数：...
Further arguments.
进一步的论据。
Details
详情----------Details----------
The algorithm first tries to identify high density regions in the data. If the input is a flowSet, density regions will be computed on the collapsed data, hence it should have been normalized before (see warpSet for one possible normalization technique). The high density regions are then clasified as positive and negative populations, based on their mean value in the theoretical (or absolute if argument absolute=TRUE) measurement range. In case there are only two high-density regions the lower one is usually clasified as the negative populations, however the heuristics in the algorithm will force the classification towards a positive population if the mean value is already very high. The absolute and borderQuant arguments can be used to control this behaviour. The split point between populations will be drawn at the value of mimimum local density between the two populations, or, if the alpha argument is used, somewhere between the two populations where the value of alpha forces the point to be closer to the negative (0 - 0.5) or closer to the positive population (0.5 - 1).
该算法首先尝试，以确定数据的高密度区域。如果输入的是一个flowSet，密度区域将在倒塌的数据计算，因此，它应该已经标准化之前（见warpSet一个可能的标准化技术）。高密度的区域，然后clasified正面和负面的人群，其平均值的基础上的理论（或绝对的，如果参数absolute=TRUE）测量范围。万一有只有两个高密度较低的人通常为阴性人群clasified区域，但是在算法的启发式将迫使朝积极的人口分类，如果平均值已经非常高。 absolute和borderQuant参数，可以用来控制这种行为。种群之间的分割点，将在mimimum局部密度值绘制的两个群体之间，或者，如果alpha参数，介于alpha值强制点，以更接近的两个群体负（0 - 0.5）或接近正面的人口（0.5 - 1）。
If there is only a single high-density region, the algorithm will fall back to estimating the mode of the distribution (hubers) and a robust measure of it's variance and, in combination with the sd argument, set the split point somewhere in the right or left tail, depending on the classification of the region.
如果只有一个单一的高密度区域，该算法将回落估计的分布模式（hubers）和它的变异的稳健措施相结合，与sd参数，设置分割点的地方在左或右的尾巴，取决于该区域的分类。
For more than two populations, the algorithm will still classify each population into positive and negative and compute the split point between those clusteres, similar to the two population case.
对于两个以上的人口，该算法仍然分为正面和负面的每个人口计算分割点，之间的clusteres的两个人口情况相似。
The rangeFilter class and constructor provide the means to treat rangeGate as regular flowCore filters.
rangeFilter类和构造提供的手段对待rangeGate常规flowCore过滤器。
值----------Value----------
A range gate, more explicitely an object of class rectangleGate.
一个范围内的门，更明确地类rectangleGate的对象。
方法----------Methods----------
%in% signature(x = "flowFrame", table = "rangeFilter"): the work horse for doing the actual filtering. Internally, this simply calls the rangeGate
在％signature(x = "flowFrame", table = "rangeFilter")：做实际的过滤工作马。在内部，这只是调用rangeGate
作者（S）----------Author(s)----------
Florian Hahne, Kyongryun Lee
参见----------See Also----------
warpSet, rangeGate, rectangleGate
warpSet，rangeGate，rectangleGate
举例----------Examples----------
data(GvHD)
dat <- GvHD[pData(GvHD)$Patient==10]
dat <- transform(dat, "FL4-H"=asinh(`FL4-H`), "FL3-H"=asinh(`FL3-H`))
rg <- rangeGate(dat, "FL4-H", plot=TRUE)
rg
split(dat, rg)
## Test rangeGate when settting refLine=0; it does not do anything since[当settting refLine＃测试rangeGate“= 0;它不会做任何事情，因为]
## there is no sub-population below zero.[＃有子的人口不低于零。]
rangeGate(dat, "FL4-H", plot=FALSE, refLine=0)
rf <- rangeFilter("FL4-H")
filter(dat, rf)
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 18:10:59
