pics-class(PICS)
pics-class()所属R语言包：PICS
The pics class
太平洋岛国类
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This object is used to gather all parameters from fitting PICS to a single candidate region. The objet contains the following slots: 'estimates', 'infMat', 'Nmerged', 'converge', 'chr'. 'estimates' is a list containing all parameters estimates as well as standard errors. 'infMat' is the Cholesky decomposition of the information matrix, 'converge' is a logical value indicating whether the EM algorithm has converged, while 'chr' is a character string corresponding to a candidate region's chromosome. 'Nmerged' gives the number of binding events that were merged; binding events that overlap are merged (see the cited paper below for details).
此对象用于收集所有参数拟合的PICS到一个单一的候选区域。客体包含以下插槽：“估计”，“infMat，”Nmerged的，收敛，字符。 “估计”是一个列表，包含所有参数估计以及标准错误。 “infMat是信息矩阵的Cholesky分解，”衔接“是一个逻辑值，指示是否EM算法收敛，而”CHR“是一个字符串对应一个候选区域的染色体。 “Nmerged给出的结合，合并事件，合并重叠的绑定事件（见引论文，详情如下）。
存取----------Accessors----------
The PICS package provide accessors to directly access to most of the parameters/standard errors and chromosome. In the code snippets below, 'x' is a 'pics' object.
太平洋岛国包提供访问器直接访问参数/标准错误和染色体。在下面的代码片段，X是图片的对象。
"chromosome(x)" Gets the chromosome name of the candidate region.
“染色体（X）”获取染色体候选区域的名称。
"mu(x)" Gets the position estimates of all binding sites identified in the region.
“万亩（X）获取确定在该区域的所有结合位点的位置估计。
"delta(x)" Gets the average fragment lengths of all binding sites identified in the region.
“Delta（X）获取确定在该区域的所有结合位点的平均片段长度。
"sigmaSqF(x)" Gets the F peak variances of all binding sites identified in the region.
“sigmaSqF（X）获取确定在该区域的所有结合位点的F峰差异。
"sigmaSqR(x)" Gets the R peak variances of all binding sites identified in the region.
“sigmaSqR（X）获取确定在该区域的所有结合位点的R峰差异。
"seF(x)" Gets the standard errors of all binding site position estimates identified in the region.
“两会（X）获取所有结合位点的位置，估计在该区域所确定的标准错误。
"seF(x)" Gets the standard errors of all F peak modes identified in the region.
“两会（X）获取高峰确定在该区域的所有F模式的标准误差。
"seR(x)" Gets the standard errors of all R peak modes identified in the region.
SER（X）“获取所有的R峰模式，确定在该区域的标准误差。
score signature(x = "pics"): return the score for each binding event.
得分signature(x = "pics")：返回每个绑定事件的得分。
scoreF signature(x = "pics"): return the score of the forward (F) for each binding event.
scoreFsignature(x = "pics")：返回的前锋（F）的得分为每个绑定事件。
scoreR signature(x = "pics"): return the score of the forward (R) for each binding event.
射手signature(x = "pics")：返回的前锋得分（R）的每个绑定事件。
构造----------Constructor----------
newPics(w,mu,delta,sigmaSqF,sigmaSqR,seMu,seMuF,seMuR,score,Nmerged,converge,infMat,chr) construct a new 'pics' object with the following arguments:
newPics（W，亩，Delta，sigmaSqF，sigmaSqR，色目人，seMuF，seMuR，得分，Nmerged，收敛，infMat，CHR）构造一个新的“图片”对象，使用下面的参数：
w The mixture weights (a vector)
W的混合物重量（向量）
mu The binding site positions (a vector)
亩结合位点的位置（向量）
delta The DNA fragment lengths (a vector)
Delta的DNA片段长度（向量）
sigmaSqF The variance parameters for the forward distribution (vector)
sigmaSqF向前分布的方差（矢量）参数
sigmaSqR The variance parameters for the forward distribution (vector)
sigmaSqR方差参数的正向分布（矢量）
seMu The standard errors for mu (vector)
SEMU亩的标准误差（矢量）
seMuF The standard errors for muF (vector)
seMuF MUF的标准误差（矢量）
seMuR The standard errors for muR (vector)
seMuR穆尔的标准误差（矢量）
seMuR The standard errors for muR (vector)
seMuR穆尔的标准误差（矢量）
score The scores for each binding event (vector)
得分的分数为每个绑定事件（矢量）
Nmerged The number of peaks that got merged (integer)
Nmerged得到合并峰（整数）
converge A logical value, TRUE, if the EM as converged
收敛一个逻辑值TRUE，如果作为融合的EM
infMat The information matrix
infMat的信息矩阵
chr The chromosome for the region
CHR在该区域的染色体
作者（S）----------Author(s)----------
Xuekui Zhang, Arnaud Droit <<a href="mailto:arnaud.droit@crchuq.ualaval.ca">arnaud.droit@crchuq.ualaval.ca</a>> and Raphael Gottardo <<a href="mailto:rgottard@fhcrc.org">rgottard@fhcrc.org</a>>
参考文献----------References----------
参见----------See Also----------
pics picsError
picspicsError
举例----------Examples----------
# Here is an example of how to construct such a region.[下面是一个例子，如何建立这样一个区域。]
# Typically, you would not do this manually, you would use the pics function to return a 'picsList' that contains a list of 'pics' or a 'picsError' object.[通常情况下，你会不会做手工，你会使用图片功能返回一个picsList“包含了”图片“或”picsError对象名单。]
w<-1
mu<-10000
delta<-150
sigmaSqF<-5000
sigmaSqR<-5000
seMu<-10
seMuF<-10
seMuR<-10
score<-5
Nmerged<-0
converge<-TRUE
chr<-"chr1"
range<-c(1000,2000)
# Contructor[构造器]
#myPICS<-newPics(w,mu,delta,sigmaSqF,sigmaSqR,seMu,seMuF,seMuR,score,Nmerged,as.integer(range),chr)[]
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 2012-2-26 11:07:19
