getProfiles(Starr)
getProfiles()所属R语言包：Starr
Get profiles of ChIP-signal over annotated features
注释功能，得到型材的芯片信号
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function associates the measured ChIP signals to annotated features and stores the profile of each feature in a list. Each profile is divided in three parts. The first entry is ”upstream”, which saves the signal upstream of start. Then follows ”region”, which is from start to end and then ”downstream”, which stores the signals downstream of end.
此功能相关联的测量芯片的信号注释功能和存储的文件列表中的每个功能。每个配置文件分为三个部分。第一项是“上游”的开始，从而节省了上游的信号。接着“区域”，这是从开始到结束，然后“下游”，其中存储月底下游的信号。
用法----------Usage----------
getProfiles(eSet, probeAnno, gffAnno, upstream, downstream, feature="ORF", borderNames, method, sameLength=T, fill=T, distance=8, spacing=4)
参数----------Arguments----------
参数：eSet
an ExpressionSet, containing on sample.
ExpressionSet，样品中含有。
参数：probeAnno
a probeAnno object for the given ExpressionSet
为给ExpressionSet probeAnno对象
参数：gffAnno
a data frame containing the annotation of the features of interest
一个数据框包含感兴趣的功能注释
参数：upstream
how many basepairs upstream of the feature start (feature start on the crick strand is end in gffAnno) should be taken.
应采取多少个碱基对的功能开始（克里克链上的功能开始年底在gffAnno）上游。
参数：downstream
how many basepairs downtream of the feature start (feature end on the crick strand is start in gffAnno) should be taken.
应采取多少个碱基对的功能开始（克里克链上的功能到底是在gffAnno开始）downtream。
参数：feature
name of the features (e.g. ORF, transcript, rRNA, ...)
的功能名称（如框，成绩单，rRNA基因，...）
参数：borderNames
names of the borders, flaking the feature (e.g. c("start", "stop"))
边界的名称，剥落的功能（例如：C（“开始”，“一站式”））
参数：method
Two methods are available. "middle", just takes the middle position of each probe and its corresponding value. This method should be used if the whole genome is tiled in an high resolution. "basewise" calculates for each base the mean of all probes overlapping with this position.
两种方法都可用。 “中间”，只需要每个探针和其相应价值的中间位置。如果平铺在一个高分辨率的全基因组，应使用此方法。 “basewise”这个位置重叠的所有探针的平均值计算每个碱基。
参数：fill
if "middle" is chosen the distance of the taken values equals the probe spacing on the chip. To avoid errors, because of regions lacking of probes, one can fill up these regions with NAs.
如果选择了“中间”所采取的值的距离等于芯片上的探针间距。为了避免错误，因为缺乏区域的探针，可以填补这些区域的NAS。
参数：distance
if method "middle" and fill==TRUE are chosen, distance is the max distance of no value occuring before filling in one NA.
如果方法为“中等”和填充== TRUE的选择，距离没有发生填写1不适用前值的最大距离。
参数：spacing
probe spacing on the chip. Only used for filling up with NAs in method "middle".
在芯片上的探针间距。仅用于灌装与NAS在“中间”的方法。
参数：sameLength
if method "middle" is chosen it can occur that the length of the upstream/downstream region vary a little. If sameLength==TRUE, upstream/downstream regions get all the same length.
如果选择“中间”的方法，它可以发生的上游/下游区域的长度有点不同。如sameLength == TRUE时，上游/下游区域得到相同的长度。
值----------Value----------
a list with the following entries
以下条目列表
参数：ID
the ID/name of the sample
样品编号/名称
参数：upstream
number of basepairs, taken upstream of the feature
碱基对的数量，采取上游的功能
参数：downstream
number of basepairs, taken upstream of the feature
碱基对的数量，采取上游的功能
参数：method
method used
使用的方法
参数：borderNames
names of the borders
边界的名称
参数：feature
feature type (e.g. "ORF")
功能类型（例如，“框”）
参数：profile
a list which contains all profiles of the features in the gffAnno. Each entry consists of a list with the elements "upstream", "region", "downstream".
这包含在gffAnno功能的所有配置文件的列表。每个条目包含一个“上游”的元素的列表，“区域”，“下游”。
作者（S）----------Author(s)----------
Benedikt Zacher <a href="mailto:zacher@lmb.uni-muenchen.de">zacher@lmb.uni-muenchen.de</a>
参见----------See Also----------
fill,fillNA,mapFeatures,getIntensities,getFeature,
fill，fillNA，mapFeatures，getIntensities，getFeature
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）]
# transcriptAnno <- read.gffAnno(file.path(dataPath, "transcriptAnno.gff"), feature="transcript")[transcriptAnno < - read.gffAnno（file.path功能=（数据通路，“transcriptAnno.gff”），“成绩单”）]
# profile <- getProfiles(rpb3_rankpercentile_ratio, probeAnnoChr1, transcriptAnno, 500, 500, feature="transcript", borderNames=c("TSS", "TTS"), method="basewise", sameLength=T, fill=T, distance=8, spacing=4)[个人资料< - getProfiles（rpb3_rankpercentile_ratio，probeAnnoChr1，transcriptAnno，500，500，功能=“成绩单”，borderNames = C（“TSS的”，“语音合成”），方法=“basewise的”，sameLength距离= T，填充= T = 8，间距= 4）]
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 2012-2-26 15:08:32
