flowFPPlex(flowFP)
flowFPPlex()所属R语言包：flowFP
Fingerprint collection constructor.
指纹采集器的构造。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This constructor creates a flowFPPlex, which is a collection of flowFPs.
此构造函数创建一个flowFPPlex，这是一个集合flowFPs。
用法----------Usage----------
flowFPPlex(fingerprints = NULL)
参数----------Arguments----------
参数：fingerprints
List of flowFPs, or NULL. If NULL an empty flowFPPlex will be prepared, to which flowFPs may be added with append-methods.
名单flowFPs，或NULL。将准备如果为NULL空flowFPPlex，flowFPs可加用追加的方法。
Details
详情----------Details----------
A flowFPPlex is a container object for a collection of flowFPs. It is useful in several ways. First, multiple-tube panels are often used to assay more reagents than can be done on a particular instrument. Second, it is sometimes useful to represent the same data with multiple flowFPModels.
在一个flowFPPlex是一个的flowFPs集合的容器对象。它是有用的几种方式。第一，多管板通常用于可以超过一个特定的仪器上进行检测试剂。其次，它有时是有用，以与多个flowFPModels代表相同的数据。
Suppose that we have collected data from 1,000 patients, using an 8-tube panel. Imagine that Tubes 1 and 8 are isotype and viability tubes, respectively (we will ignore these tubes for now). The remaining Tubes 2-7 are of interest from a fingerprinting perspective. We wish to treat them as a unit. We might then create models that represent parameters in each of the tubes, across some (or all) of the patient samples (say, mod2, mod3, ..., mod7). We could then create corresponding flowFPs (say, fp2, fp3, ..., fp7). These can now be combined and treated as a single object of type flowFPPlex, as:
假设，我们所收集的数据来自1000名患者，使用8管的面板。试想一下，1和8管亚型和活力管，分别为（我们现在将忽略这些管子）。其余管2-7从指纹角度的利益。我们希望把它们作为一个单元。然后，我们可能创建在每个管参数的模型表示，遇到一些病人样本（或全部），（比方说，MOD2，mod3，...，mod7）。然后我们就可以创建相应的flowFPs（比方说，FP2，FP3，...，FP7）。这些现在可以进行组合和单一的对象作为类型flowFPPlex的处理，如：
> plex <- flowFPPlex(c(fp2, fp3, fp4, fp5, fp6, fp7))<br><br> or if you prefer,<br><br> > plex <- flowFPPlex (fingerprints=NULL)<br> > plex <- append(plex, c(fp2, fp3, fp4, fp5, fp6, fp7))
> plex <- flowFPPlex(c(fp2, fp3, fp4, fp5, fp6, fp7))参考参考，或者如果你喜欢，参考参考> plex <- flowFPPlex (fingerprints=NULL)参考> plex <- append(plex, c(fp2, fp3, fp4, fp5, fp6, fp7))
The counts or density matrices can then be extracted simply using methods provided in flowFPPlex-class.
然后可以使用在flowFPPlex级提供的方法提取简单的数量或密度矩阵。
The second idea is to use multiple models to represent the same data. In this case we might create a model from, say, the "Normal" instances (call it mod\_norm), and another model from the "Cancer" instances (mod\_cancer). We might wish to do this to enhance the detection of regions of the distribution that are characteristically dominated by one type or the other. If our flowSet of all instances is called "fs1", then our two representations would be:
第二个想法是使用多个模型来表示相同的数据。在这种情况下，我们可能会创建一个模型，说，“正常”的实例（叫它MOD \ _norm），另从“癌症”的实例（MOD \ _cancer）的模型。我们不妨这样做是为了加强区域的分布，是典型的一种类型或其他主导的检测。如果我们的所有实例flowSet的是称为“FS1”，那么我们将两种表示：
> fp_norm <- flowFP (fs1, mod_norm)<br> > fp_cancer <- flowFP (fs2, mod_cancer)
> fp_norm <- flowFP (fs1, mod_norm)参考> fp_cancer <- flowFP (fs2, mod_cancer)
and the plex is
和复杂的是
plex <- flowFPPlex (c(fp_norm, fp_cancer))
plex <- flowFPPlex (c(fp_norm, fp_cancer))
值----------Value----------
Returns a flowFPPlex.
返回一个flowFPPlex。
作者（S）----------Author(s)----------
Herb Holyst <<a href="mailto:holyst@mail.med.upenn.edu">holyst@mail.med.upenn.edu</a>>, Wade Rogers <<a href="mailto:rogersw@mail.med.upenn.edu">rogersw@mail.med.upenn.edu</a>>
参见----------See Also----------
flowFPPlex-class, flowFP
flowFPPlex级，flowFP
举例----------Examples----------
data(fs1)
data(fs2)
mod1 <- flowFPModel (fs1, parameters=c(2,5))
mod2 <- flowFPModel (fs2, parameters=c(2,5))
fp1_1 <- flowFP (fs1, mod1)
fp1_2 <- flowFP (fs1, mod2)
plex <- flowFPPlex(c(fp1_1, fp1_2))
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。
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发表于 2012-2-25 17:52:59
