readBins(mosaics)
readBins()所属R语言包：mosaics
Import bin-level ChIP-sep data
导入斌级芯片九月数据
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Import and preprocess all or subset of bin-level ChIP-sep data, including ChIP data, control data, mappability score, GC content score, and sequence ambiguity score.
导入和预处理全部或子集的bin级芯片的SEP数据，包括芯片的数据，控制数据，mappability得分，GC含量得分，和序列模糊得分。
用法----------Usage----------
readBins( type = c("chip", "M", "GC", "N"), fileName = NULL,
excludeChr=NULL, dataType = "unique", rounding = 100, parallel=FALSE, nCore=8 )
参数----------Arguments----------
参数：type
Character vector indicating data types to be imported. This vector can contain "chip" (ChIP data), "input" (input data), "M" (mappability score), "GC" (GC content score), and "N" (sequence ambiguity score). Currently, readBins permits only the following combinations: c("chip", "input", "M", "GC", "N"), c("chip", "M", "GC", "N"), c("chip", "input", "N"), and c("chip", "input"). Default is c("chip", "M", "GC", "N").
需要进口的特征向量表示的数据类型。这个向量可以包含"chip"（芯片的数据），"input"（输入数据），"M"（得分mappability），"GC"（GC含量得分），和"N" （序列歧义得分）。目前，readBins只允许以下组合：c("chip", "input", "M", "GC", "N")，c("chip", "M", "GC", "N")，c("chip", "input", "N")，c("chip", "input")。默认c("chip", "M", "GC", "N")。
参数：fileName
Character vector of file names, each of which matches each element of type. type and fileName should have the same length and corresponding elements in two vectors should appear in the same order.
字符的文件名的向量，其中每个type每个元素相匹配。 type和fileName应该有相同的长度和两个向量的对应元素应该会出现在相同的顺序。
参数：excludeChr
Vector of chromosomes that are excluded from the analysis.
从分析中排除染色体的向量。
参数：dataType
How reads were processed? Possible values are either "unique" (only uniquely aligned reads were retained) or "multi" (reads aligned to multiple locations were also retained).
读了如何处理？可能的值是要么"unique"（只有唯一对准读取保留）或"multi"（读取对齐多个地点也被保留下来）。
参数：rounding
How are mappability score and GC content score rounded? Default is 100 and this indicates rounding of mappability score and GC content score to the nearest hundredth.
如何mappability得分和GC含量得分四舍五入？默认是100，这表明的mappability得分和GC含量比分最接近的百分位四舍五入。
参数：parallel
Utilize multiple CPUs for parallel computing using "multicore" package? Possible values are TRUE (use "multicore") or FALSE (not use "multicore"). Default is FALSE (not use "multicore").
利用多个CPU并行计算使用"multicore"包？可能的值是TRUE（"multicore"）FALSE（不使用"multicore"）。默认是FALSE（不使用"multicore"）。
参数：nCore
Number of CPUs when parallel computing is utilized.
利用并行计算时的CPU的数量。
Details
详情----------Details----------
Bin-level ChIP and input data can be generated from the aligned read files for your samples (e.g., files obtained from the ELAND aligner) using the method constructBins. In mosaics package companion website, http://www.stat.wisc.edu/~keles/Software/mosaics/, we provide preprocessed mappability score, GC content score, and sequence ambiguity score files for diverse reference genomes. Please check the website and the vignette for further details.
斌级芯片和输入数据，可以生成从样品对齐的读文件，使用方法constructBins（例如，从伊兰对准取得的文件）。在mosaics包同伴网站，http://www.stat.wisc.edu/~keles /软件/马赛克/我们提供了多样化的参考基因组预处理mappability得分，GC含量得分，序列模糊得分文件。请检查网站，并为进一步的细节的小插曲。
The imported data type constraints the analysis that can be implemented. If type=c("chip", "M", "GC", "N"), only one-sample analysis is permitted. If type=c("chip", "input") or c("chip", "input", "N"), only two-sample analysis without using mappability and GC content is possible. For type=c("chip", "input", "M", "GC", "N"), user can do all the one- or two-sample analysis. See also help page of mosaicsFit.
导入的数据类型约束的分析，可以实现。如果type=c("chip", "M", "GC", "N")，只有一个样品的分析是允许的。如果type=c("chip", "input")或c("chip", "input", "N")，只有两个样本不使用mappability和GC含量分析是可能的。 type=c("chip", "input", "M", "GC", "N")，用户可以做一个或两个样品的分析。也有助于mosaicsFit页。
When the data contains multiple chromosomes, parallel computing can be utilized for faster preprocessing if parallel=TRUE and multicore package is installed. nCore determines number of CPUs used for parallel computing.
当数据包含多个染色体，并行计算，可以用于更快的预处理，如果parallel=TRUE和multicore包安装。 nCore确定用于并行计算的CPU数量。
值----------Value----------
Construct BinData class object.
构建BinData类的对象。
作者（S）----------Author(s)----------
Dongjun Chung, Pei Fen Kuan, Sunduz Keles
参考文献----------References----------
"A Statistical Framework for the Analysis of ChIP-Seq Data", Journal of the American Statistical Association, Vol. 106, pp. 891-903.
参见----------See Also----------
constructBins, mosaicsFit, BinData.
constructBins，mosaicsFit，BinData。
举例----------Examples----------
## Not run: [＃无法运行：]
library(mosaicsExample)
exampleBinData <- readBins( type=c("chip","input","M","GC","N"),
fileName=c( system.file("extdata/chip_chr21.txt", package="mosaicsExample"),
system.file("extdata/input_chr21.txt", package="mosaicsExample"),
system.file("extdata/M_chr21.txt", package="mosaicsExample"),
system.file("extdata/GC_chr21.txt", package="mosaicsExample"),
system.file("extdata/N_chr21.txt", package="mosaicsExample") ) )
## End(Not run)[＃结束（不运行）]
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 01:08:30
