cmarrt.peak(Starr)
cmarrt.peak()所属R语言包:Starr
Obtain bound regions for a given error rate control
结合区域获得一个给定的错误率控制
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Obtain bound regions under a given error rate control using correction method from p.adjust.
下获得一个给定的错误率控制使用校正法从p.adjust绑定区域。
用法----------Usage----------
cmarrt.peak(cmarrt.ma, alpha, method, minrun, asCherList=FALSE)
参数----------Arguments----------
参数:cmarrt.ma
output object from cmarrt.ma.
从cmarrt.ma输出对象。
参数:alpha
error rate control for declaring bound region.
声明绑定区域的错误率控制。
参数:method
correction method inherited from p.adjust.
从p.adjust继承的修正方法。
参数:minrun
minimum number of probes to be called a bound region.
被称为绑定区域的探针的最低数量。
参数:asCherList
If TRUE, result is returned as class cherList. See Ringo, for further description.
如果为TRUE,结果返回类cherList的。看到林檎,为进一步的说明。
Details
详情----------Details----------
The function returns two objects, cmarrt.bound and indep.bound. Each object is a list of bound regions which can be accessed by $chr (chromosome), $peak.start (start coordinate of each bound region), $peak.stop (stop coordinate of each bound region),
该函数返回两个对象,cmarrt.bound和indep.bound。每个对象是一个$chr(染色体),$peak.start(开始坐标方向各区域),$peak.stop(停止方向各区域的协调),它可以访问的束缚区域名单
值----------Value----------
参数:cmarrt.bound
list of bound regions obtained under correlation structure.
相关结构下获得的束缚区域的名单。
参数:indep.bound
list of bound regions obtained under independence (ignoring correlation).
独立(忽略相关)下获得的束缚区域的名单。
注意----------Note----------
The list of bound regions obtained under independence (ignoring the correlation structure) is for comparison. It is not recommended to use this list for downstream analysis.
束缚下独立获得的区域名单(忽略相关结构)进行比较。这是不推荐使用此列表中,下游分析。
作者(S)----------Author(s)----------
Pei Fen Kuan, Adam Hinz
参考文献----------References----------
<h3>See Also</h3>
举例----------Examples----------
# dataPath <- system.file("extdata", package="Starr")[< - 。系统数据通路(的“extdata”,包=“斯塔尔”)]
# bpmapChr1 <- readBpmap(file.path(dataPath, "Scerevisiae_tlg_chr1.bpmap"))[bpmapChr1 < - readBpmap(file.path(数据通路,“Scerevisiae_tlg_chr1.bpmap”))]
# cels <- c(file.path(dataPath,"Rpb3_IP_chr1.cel"), file.path(dataPath,"wt_IP_chr1.cel"), [CELS < - C(file.path(数据通路,“Rpb3_IP_chr1.cel”),file.path(数据通路,“wt_IP_chr1.cel”),]
# file.path(dataPath,"Rpb3_IP2_chr1.cel"))[file.path(数据通路,“Rpb3_IP2_chr1.cel”))]
# names <- c("rpb3_1", "wt_1","rpb3_2")[名< - (“rpb3_1”,“wt_1”,“rpb3_2”)]
# type <- c("IP", "CONTROL", "IP")[类型< - C(“知识产权”,“控制”,“知识产权”)]
# rpb3Chr1 <- readCelFile(bpmapChr1, cels, names, type, featureData=TRUE, log.it=TRUE)[rpb3Chr1 < - readCelFile(bpmapChr1,CELS,名称,类型,featureData = TRUE,log.it = TRUE)]
# ips <- rpb3Chr1$type == "IP"[IPS <费用 - rpb3Chr1类型==“知识产权”]
# controls <- rpb3Chr1$type == "CONTROL"[控制<“ - rpb3Chr1 $ ==”控制“]
# rpb3_rankpercentile <- normalize.Probes(rpb3Chr1, method="rankpercentile")[rpb3_rankpercentile < - normalize.Probes(rpb3Chr1,方法=“rankpercentile”)]
# description <- c("Rpb3vsWT")[说明< - Ç(“Rpb3vsWT”)]
# rpb3_rankpercentile_ratio <- getRatio(rpb3_rankpercentile, ips, controls, description, fkt=median, featureData=FALSE)[rpb3_rankpercentile_ratio < - getRatio(rpb3_rankpercentile,IPS,控制,描述,FKT =中位数,featureData = FALSE)]
# probeAnnoChr1 <- bpmapToProbeAnno(bpmapChr1)[probeAnnoChr1 < - bpmapToProbeAnno(bpmapChr1的)]
# peaks <- cmarrt.ma(rpb3_rankpercentile_ratio, probeAnnoChr1, chr=NULL, M=NULL,250,window.opt='fixed.probe')[峰< - cmarrt.ma(rpb3_rankpercentile_ratio,probeAnnoChr1,CHR = NULL,M = NULL,250,window.opt =fixed.probe)]
# peaklist <- cmarrt.peak(peaks)[< - cmarrt.peak peaklist(峰)]
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注:
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