islandCounts(htSeqTools)
islandCounts()所属R语言包：htSeqTools
Find genomic regions with high coverage and count number of reads
高覆盖率的基因组区域，并计算读取数
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Finds genomics regions where the coverage is above a user-specified threshold and counts the number of ranges in each sample overlapping each region.
发现基因组区域覆盖上述用户指定的阈值，并计算每个样品的数量不等，每个区域重叠。
用法----------Usage----------
islandCounts(x, minReads=10, mc.cores=1)
参数----------Arguments----------
参数：x
RangedData or RangedDataList containing the reads. If a RangedDataList is provided, the overall coverage across all its elements is used to find the regions of interest, but individual counts are computed for each element in the list.
RangedData或RangedDataList包含的内容。如果RangedDataList提供，其所有元素的整体覆盖面是用来寻找感兴趣的区域，但个别计数计算列表中的每个元素。
参数：minReads
Only regions with coverage above minReads are considered.
只以上minReads覆盖区域被视为。
参数：mc.cores
If mc.cores>1 computations are performed in parallel, using function mclapply from package multicore.
如果mc.cores>1计算并行执行，从使用功能mclapply包multicore。
Details
详情----------Details----------
The output of islandCounts can be the input data for a number of downstream analysis methods. Although for a simple-minded analysis one could use enrichedRegions, one will usually want to use more sofisticated analyses (e.g. from packages DEseq, BayesPeak, limma etc.)
islandCounts输出可以是下游的分析方法输入数据。虽然一个头脑简单的分析，可以使用enrichedRegions，人们通常会要使用（例如包DEseq，BayesPeak，limma等）更sofisticated的分析
值----------Value----------
Object of class RangedData indicating the regions with coverage above minReads and the number of reads overlapping each sample for those regions.
Object类的RangedData说明与以上minReads“重叠读取每个样品为这些区域的覆盖区域。
方法----------Methods----------
x is assumed to contain the reads from a single sample. Genomic regions with high coverage will be detected and the number of reads overlapping these regions will be computed.
x假设包含了从单一样本的读取。将被检测基因组高覆盖的区域，将计算和读取这些区域重叠。
x is assumed to contain the reads for several samples, one sample in each element of the list. The overall coverage across all samples is computed by adding the coverage in the individual samples, and the regions with overall coverage above the user-specified threshold are selected. Then the number of reads overlapping each region is computed.
x被认为包含几个样本，一个样本的读取列表中的每个元素。个别样品中添加覆盖所有样品的整体覆盖率计算，并选择与用户指定的阈值以上的整体覆盖的区域。然后读取每个区域重叠的数量计算。
举例----------Examples----------
set.seed(1)
st <- round(rnorm(1000,500,100))
strand <- rep(c('+','-'),each=500)
space <- rep('chr1',length(st))
sample1 <- RangedData(IRanges(st,st+38),strand=strand,space=space)
st <- round(rnorm(1000,1000,100))
sample2 <- RangedData(IRanges(st,st+38),strand=strand,space=space)
regions <- islandCounts(RangedDataList(sample1,sample2),minReads=50)
regions
#Plot coverage[图覆盖率]
plot(coverage(sample1)[[1]],type='l',xlim=c(0,2000))
lines(coverage(sample2)[[1]],col=2)
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 2012-2-25 22:03:43
