processAD(segmentSeq)
processAD()所属R语言包：segmentSeq
Processes an ‘alignmentData’ object into a ‘segData’ object for segmentation.
处理到“segData”对象分割alignmentData“对象。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
In order to discover segments of the genome with a high density of sequenced data, a "segData" object must be produced. This is an object containing a set of potential segments, together with the counts for each sample in each potential segment.
为了发现段的基因组的测序数据的高密度，“segData对象必须出示。这是一个对象，它包含了一套潜在的段，在每个潜在段的每个样品计数。
用法----------Usage----------
processAD(aD, gap = NULL, verbose = TRUE, cl)
参数----------Arguments----------
参数：aD
An alignmentData object.
alignmentData对象。
参数：gap
The maximum gap between aligned tags that should be allowed in constructing potential segments. See Details.
对齐，应在建设潜力段允许的标签之间的最大差距。查看详细信息。
参数：verbose
Should processing information be displayed? Defaults to TRUE.
要处理的信息显示吗？默认为true。
参数：cl
A SNOW cluster object, or NULL. See Details.
雪聚类对象，或NULL。查看详细信息。
Details
详情----------Details----------
This function takes an alignmentData object and constructs a segData object from it. The function creates a set of potential segments by looking for all locations on the genome where the start of a region of overlapping alignments exists in the alignmentData object. A potential segment then exists from this start point to the end of all regions of overlapping alignments such that there is no region in the segment of at least length "gap" where no tag aligns. The number of potential segments can therefore be increased by increasing this limit, or (usually more usefully) decreased by decreasing this limit in order to save computational effort.
这个函数需要一个alignmentData对象，并从它构造一个segData对象。函数创建了一套潜在的分部，通过寻找区域重叠的路线开始在alignmentData对象存在的基因组上的所有位置。一个潜在的部分则存在从这个起点到年底所有区域重叠的路线，这样有没有段的长度至少有“差距”没有标记对齐区域。增加此限制，因此可以增加一些潜在的细分，或（通常是更有益的）下降减少此限制，以节省计算的努力。
The "gap" argument is now by default specified in the readGeneric and readBAM functions used to create the "aD" object, and so "gap" can be left as NULL providing this has been done.
差距的说法是现在由readGeneric和readBAM函数用于创建广告的对象，所以“差距”，指定默认可以提供这一直留为NULL完成。
A 'cluster' object (package: snow) is recommended for parallelisation of this function when using large data sets. Passing NULL to this variable will cause the function to run in non-parallel mode.
一个'cluster'对象（包雪）建议使用大型数据集时，此功能的并行化。这个变量传递NULL会导致在非并行模式运行的功能。
值----------Value----------
A segData object.
一个segData对象。
作者（S）----------Author(s)----------
Thomas J. Hardcastle
参见----------See Also----------
getCounts, which produces the count data for each potential segment. heuristicSeg and classifySeg, which segment the genome based on the segData object produced by this function segData alignmentData
getCounts，它为每一个潜在的段产生的计数数据。 heuristicSeg和classifySeg，即分部为基础的基因组上的segDatasegDataalignmentData此功能产生对象
举例----------Examples----------
# Define the chromosome lengths for the genome of interest.[定义感兴趣的基因组染色体长度。]
chrlens <- c(2e6, 1e6)
# Define the files containing sample information.[定义文件包含样本信息。]
datadir <- system.file("extdata", package = "segmentSeq")
libfiles <- c("SL9.txt", "SL10.txt", "SL26.txt", "SL32.txt")
# Establish the library names and replicate structure.[建立图书馆的名称和复制结构。]
libnames <- c("SL9", "SL10", "SL26", "SL32")
replicates <- c(1,1,2,2)
# Process the files to produce an `alignmentData' object.[处理文件，以生产alignmentData“对象。]
alignData <- readGeneric(file = libfiles, dir = datadir, replicates =
replicates, libnames = libnames, chrs = c(">Chr1", ">Chr2"), chrlens =
chrlens, gap = 100)
# Process the alignmentData object to produce a `segData' object.[处理的alignmentData的对象产生segData“对象。]
sD <- processAD(alignData, gap = 100, cl = NULL)
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 14:00:39
