lociLikelihoods(segmentSeq)
lociLikelihoods()所属R语言包：segmentSeq
Evaluates the posterior likelihoods of each region defined by a
评估各区域的定义后似然性
译者：生物统计家园网 机器人LoveR
描述----------Description----------
An empirical Bayesian approach that takes a segmentation map and uses this to bootstrap posterior likelihoods on each region being a locus for each replicate group.
一个经验贝叶斯方法，需要分割图，对每个区域使用这个来引导后似然性，为每个复制组的轨迹。
用法----------Usage----------
lociLikelihoods(cD, aD, newCounts = FALSE, bootStraps = 1,
inferNulls = TRUE, nasZero = FALSE, usePosteriors =
TRUE, cl)
参数----------Arguments----------
参数：cD
A lociData object that defines a segmentation map.
一个lociData对象，它定义了分割图。
参数：aD
An alignmentData object.
alignmentData对象。
参数：newCounts
Should new counts be evaluated for the segmentation map in "cD" before calculating loci likelihoods? Defaults to FALSE
应新的罪名被评价为“CD”前计算位点的似然性分割图？默认为false
参数：bootStraps
What level of bootstrapping should be carried out on the inference of posterior likelihoods? See the baySeq function getLikelihoods.NB for a discussion of bootstrapping.
应引导水平后似然性推理进行了吗？见的baySeq功能getLikelihoods.NB为引导讨论。
参数：inferNulls
Should null regions be inferred from the gaps between segments defined by the "cD" object?
可以推断应该空区域从“CD”对象定义的段之间的差距呢？
参数：nasZero
If FALSE, any locus with a posterior likelihood "NA" in the existing segmentation map is treated as a null region for the first bootstrap; If TRUE, it is ignored for the first bootstrap.
如果为FALSE，任何与后验的可能性“NA”在现有的分割图的轨迹视为一个空区域为第一引导，如果属实，这是第一引导忽略。
参数：usePosteriors
If TRUE, the function uses the existing likelihoods to weight the prior estimation of parameters. Defaults to TRUE.
如果为TRUE，函数使用现有的似然性，重量参数事先估计。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----------
A 'cluster' object (package: snow) may be used for parallelisation of this function when examining 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），可用于研究大型数据集时，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 lociData object.
一个lociData对象。
作者（S）----------Author(s)----------
Thomas J. Hardcastle
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, cl = NULL)
# Use the segData object to produce a segmentation of the genome, but[使用segData对象产生的基因组的分割，但]
# without evaluating posterior likelihoods.[没有评估后的似然性。]
segD <- heuristicSeg(sD = sD, aD = alignData,
subRegion = data.frame(chr= ">Chr1", start = 1, end = 1e5),
getLikes = FALSE, cl = NULL)
# Use the lociData function to evaluate the posterior likelihoods directly.[使用lociData功能，直接以评估后的似然性。]
lociData <- lociLikelihoods(segD, aD = alignData, bootStraps = 5,
inferNulls = TRUE, 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 14:00:20
