RSeed-class(RSeed)
RSeed-class()所属R语言包：RSeed
Class "RSeed"
类“RSeed”
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Datastructure to perform Borenstein algorithm and save results.
数据结构到执行鲍仁斯坦算法，并保存结果。
类对象----------Objects from the Class----------
Objects can be created by calls of the form new("RSeed", model, connectedComponentCutOff, currencyMetabolites). This is the startup, where the basic parameters are set. They can also be set later.
可以创建对象通过调用的形式new("RSeed", model, connectedComponentCutOff, currencyMetabolites)。这是启动时，其中的基本参数设定。它们也可以被设置购买。
插槽----------Slots----------
note: this class does only have one slot: an environment. to access data, the usere has to use the methods supplied.
注：这个类只能有一个插槽：一个环境。访问数据，usere使用提供的方法。
env: Object of class "environment"
env：对象类"environment"的
方法----------Methods----------
buildGraph signature(rs = "RSeed"):
buildGraphsignature(rs = "RSeed")：
combined_nodes signature(rs = "RSeed"): Names of the nodes, which combine metabolites.
combined_nodes signature(rs = "RSeed")：节点上，结合代谢物的名称。
combined_nodes<- signature(rs = "RSeed"): Setter method for this slot. This should not used by the user, until u really know, what ur doing!
combined_nodes < - signature(rs = "RSeed")：该插槽的setter方法。这是不应该由用户使用，直到你真的知道，你的做！
confidenceLevel signature(rs = "RSeed"): Return a confidence level for every seed compound as defined in the original paper. The threshold is 0.2.
confidenceLevel signature(rs = "RSeed")：返回的原始文件中定义的置信水平上一切结种子的化合物。该阈值是0.2。
connectedComponentCutOff signature(rs = "RSeed"): Return the cut off, until which size it is allowed to remove unconnected components from the graph. Default value is 10.
connectedComponentCutOffsignature(rs = "RSeed")：返回切断，直到它的大小，它被允许从图中删除未连接的组件。默认值是10。
connectedComponentCutOff<- signature(rs = "RSeed"): Set this Value.
connectedComponentCutOff < - signature(rs = "RSeed")：设置此值。
currencyMetabolites signature(rs = "RSeed"): metabolite IDs, which should be treated as currency metabolites and therefor be removed from the network. If this value is NULL, nothing is removed.
currencyMetabolitessignature(rs = "RSeed")：代谢物的标识，它应被视为货币代谢物，因此可以从网络中删除。如果这个值是NULL，则没有删除。
currencyMetabolites<- signature(rs = "RSeed"): Sets this slot. The replace Value has to be a character vector. The return value from 'findCurrencyMetabolites' is suitable.
currencyMetabolites < - “signature(rs = "RSeed")：设置此插槽。替换值是一个字符向量。的的返回值从“findCurrencyMetabolites”是合适的。
getSourceMetabolites signature(rs = "RSeed"): Returns a list, with the metabolite IDs of the as essential identified metabolites. Each list entry represents a source compound.
getSourceMetabolites signature(rs = "RSeed")：返回一个列表，作为基本确定代谢产物的代谢产物中的ID。每个列表项表示源化合物。
graph_network signature(rs = "RSeed"): Graph representation of the network.
graph_networksignature(rs = "RSeed")的网络的图形表示。
graph_network<- signature(rs = "RSeed"): Setter method for this slot. This should not used by the user, until u really know, what ur doing!
graph_network < - signature(rs = "RSeed")：该插槽的setter方法。这是不应该由用户使用，直到你真的知道，你的做！
graph_scc signature(rs = "RSeed"): Graph representation of the network with the nodes, which belong in one scc, aggregated to one node.
graph_sccsignature(rs = "RSeed")：图形表示的网络节点，它不属于在一个标准立方厘米，汇集到一个节点。
graph_scc<- signature(rs = "RSeed"): Setter method for this slot. This should not used by the user, until u really know, what ur doing!
graph_scc < - signature(rs = "RSeed")：该插槽的setter方法。这是不应该由用户使用，直到你真的知道，你的做！
initialize signature(.Object = "RSeed"): General initialize method. Automatically called from 'new'.
signature(.Object = "RSeed")：一般initialize方法进行初始化。从“新”的自动调用。
list_sc signature(rs = "RSeed"): Return node names of source compounds.
list_sc signature(rs = "RSeed")：返回节点名称源化合物。
list_sc<- signature(rs = "RSeed"): Setter method for this slot. This should not used by the user, until u really know, what ur doing!
list_sc < - signature(rs = "RSeed")：该插槽的setter方法。这是不应该由用户使用，直到你真的知道，你的做！
makeExperiment signature(rs = "RSeed"): Performs the whole analysis. The result is stored in the object and in addition to this a reference is returned, too.
makeExperiment signature(rs = "RSeed")：进行整体分析。该结果被存储在对象中，除了这是一个参考，也返回。
model_changes signature(rs = "RSeed"): Returns the names of removed metabolites and reactions. These metabolites were either removed because they had no connection to the biggest part in the graph, or because they were given as source metabolites. Reactions are removed if all participating metabolites were removed.
model_changessignature(rs = "RSeed")：返回除去的代谢物和反应的名称。这些代谢物被移除，因为它们没有连接到图中的最重要的一部分，或因为他们的源代谢产物。反应时删除所有参与的代谢产物被拆除。
model_changes<- signature(rs = "RSeed"): Setter method for this slot. This should not used by the user, until u really know, what ur doing!
model_changes < - signature(rs = "RSeed")：该插槽的setter方法。这是不应该由用户使用，直到你真的知道，你的做！
model_edited signature(rs = "RSeed"): The 'modelorg' after removing metabolites and reactions.
model_editedsignature(rs = "RSeed")：“modelorg”取出后，代谢产物和反应。
model_edited<- signature(rs = "RSeed"): Setter method for this slot. This should not used by the user, until u really know, what ur doing!
model_edited < - signature(rs = "RSeed")：此插槽的setter方法。这是不应该由用户使用，直到你真的知道，你的做！
model_original signature(rs = "RSeed"): The 'modelorg' from the beginning.
model_originalsignature(rs = "RSeed")：“modelorg”从一开始。
model_original<- signature(rs = "RSeed"): Setter method for this slot. This should not used by the user, until u really know, what ur doing!
model_original < - signature(rs = "RSeed")：此插槽的setter方法。这是不应该由用户使用，直到你真的知道，你的做！
plot signature(x = "RSeed", y = "missing"): Plots the graph_scc. Rgraphviz is needed.
图signature(x = "RSeed", y = "missing")的：绘制graph_scc。 rgraphviz是必要的。
scc_sizes signature(rs = "RSeed"): Sizes of the SCCs.
scc_sizes signature(rs = "RSeed")：尺寸的SCCS。
scc_sizes<- signature(rs = "RSeed"): Setter method for this slot. This should not used by the user, until u really know, what ur doing!
scc_sizes < - signature(rs = "RSeed")：此插槽的setter方法。这是不应该由用户使用，直到你真的知道，你的做！
scc signature(rs = "RSeed"): Returns a named list, which represents the aggregated nodes for every SCC (strongly connected component).
SCC signature(rs = "RSeed")：返回一个命名列表，它代表了每一个强连通分量（SCC）的聚合节点。
scc<- signature(rs = "RSeed"): Setter method for this slot. This should not used by the user, until u really know, what ur doing!
SCC - signature(rs = "RSeed")：该插槽的setter方法。这是不应该由用户使用，直到你真的知道，你的做！
sourceCompounds signature(rs = "RSeed"): Aggregates metabolites from the same SCC into a common node.
sourceCompoundssignature(rs = "RSeed")：聚集来自同一个SCC的代谢产物成一个共同的节点。
show signature(object = "RSeed"): Prints a short summary about the Object. (Called from generic 'print')
显示signature(object = "RSeed")：打印一个简短的摘要的对象。 （称为从一般的打印）
注意----------Note----------
Most slots of this object are automatically set by the algorithm and contain calculated results. So there is low sence in setting them by ur own.<br> <br> Nodenames are chosen as follows: 'n' + the number of the metabolite. So n4 would mean, that met_id(model)[4] is the represented metabolite.
大多数插槽，该对象的自动设置的算法，包含计算结果。因此，有低SENCE在乌尔自己的。<BR> <BR>节点名称的选择如下：N+代谢物的数量。因此，N4，将意味着，met_id（模型）[4]所代表的代谢物。
（作者）----------Author(s)----------
Claus Jonathan Fritzemeier<br> <clausjonathan.fritzemeier@uni-duesseldorf.de>
参考文献----------References----------
<h3>See Also</h3> <code>findCurrencyMetabolites</code>, <code>modelorg</code>
实例----------Examples----------
data(Ec_core)
ec <- new("RSeed", Ec_core)
# run the experiment[运行实验]
# calls of[叫声]
# buildGraph(ec)[buildGraph（EC）]
# sourceCompounds(ec)[sourceCompounds（EC）]
# would do the same in two steps.[会做同样的两个步骤。]
makeExperiment(ec)
# look which nodes aggregate[看的节点总]
scc(ec)
# look at source metabolites[看看源代谢物]
# (every list entry is a source compound)[（每个列表项是一个源化合物）]
getSourceMetabolites(ec)
# plot the graph[绘制图形]
plot(ec)
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 2012-9-28 21:22:16
