pcKeepCompDetect(nucleR)
pcKeepCompDetect()所属R语言包：nucleR
Auto detection of a fitted pcKeepComp param for filterFFT function
一个的拟合pcKeepComp参数为filterFFT功能自动检测
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function tries to obtain the minimum number of components needed in a FFT filter to achieve or get as close as possible to a given correlation value. Usually you don't need to call directly this function, is used in filterFFT by default.
这个函数试图获得在FFT过滤器组件需要尽可能接近给定的相关值达到或得到的最低数量。通常你并不需要直接调用此函数，在filterFFT默认情况下使用。
用法----------Usage----------
pcKeepCompDetect(data, pc.min=0.01, pc.max=0.1, max.iter=20, verbose=FALSE,
cor.target=0.98, cor.tol=1e-3, smpl.num=25, smpl.min.size=2^10, smpl.max.size=2^14)
参数----------Arguments----------
参数：data
Numeric vector to be filtered
数字矢量进行过滤
参数：pc.min, pc.max
Range of allowed values for pcKeepComp (minimum and maximum), in the range 0:1.
的为pcKeepComp（最大和最小）允许值的范围，在范围0:1。
参数：max.iter
Maximum number of iterations
最大迭代次数
参数：verbose
Extra information (debug)
额外的信息（调试）
参数：cor.target
Target correlation between the filtered and the original profiles. A value around 0.99 is recommeded for Next Generation Sequencing data and around 0.7 for Tiling Arrays.
之间的过滤和原有型材的目标相关。特别建议，为下一代测序数据约为0.7平铺阵列值约0.99。
参数：cor.tol
Tolerance allowed between the obtained correlation an the target one.
公差允许之间获得相关的一个目标。
参数：smpl.num
If data is a large vector, some samples from the vector will be used instead the whole dataset. This parameters tells the number of samples to pick.
如果data是一个大的向量，从向量一些样品将用来代替整个数据集。此参数告诉挑选的样本数。
参数：smpl.min.size, smpl.max.size
Minimum and maximum size of the samples. This is used for selection and sub-selection of ranges with meaningful values (i,e, different from 0 and NA). Power of 2 values are recommended, despite non-mandatory.
最小和最大规模的样品。这是用于选择和有意义的值（I，E，不同的0和NA）的范围内选择分。功率2值的建议，尽管是非强制性的。
参数：...
Parameters to be pass to autoPcKeepComp
参数被传递给autoPcKeepComp
Details
详情----------Details----------
This function predicts a suitable pcKeepComp value for filterFFT function. This is the recommended amount of components (in percentage) to keep in the filterFFT function to obtain a correlation of (or near of) cor.target.
此功能预测一个合适的pcKeepCompfilterFFT函数值。这是组件的推荐量（百分比），在保持获取的相关性（或附近）filterFFTcor.target功能。
The search starts from two given values pc.min, pc.max and uses linial interpolation to quickly reach a value that gives a corelation between the filtered and the original near cor.target within the specified tolerance cor.tol.
搜索从两个给定值pc.min, pc.max使用linial插值快速达到一个值，使得相关性实证分析之间的过滤和原来附近cor.target指定的公差范围内cor.tol1。
To allow a quick detection without an exhaustive search, this function uses a subset of the data by randomly sampling those regions with meaningful coverage values (i,e, different from 0 or NA) larger than smpl.min.size. If it's not possible to obtain smpl.max.size from this region (this could be due to flanking 0's, for example) at least smpl.min.size will be used to check correlation. Mean correlation between all sampled regions is used to test the performance of the pcKeepComp parameter.
为了让一个没有穷尽搜索的快速检测，此功能使用的数据的一个子集，通过随机抽样与这些区域的有意义的覆盖面值（I，E，从0或NA）较大的比smpl.min.size。如果这是不可能获得从本区域smpl.max.size（这可能是由于侧翼0的，例如，）至少smpl.min.size将被用来检查相关的。平均之间的所有抽样区域的相关使用性能测试的pcKeepComp参数。
If the number of meaningful bases in data is less than smpl.min.size * (smpl.num/2) all the data vector will be used instead of using sampling.
如果在data有意义的碱基数量少于smpl.min.size * (smpl.num/2)data向量将被用来代替使用采样。
值----------Value----------
Fitted pcKeepComp value
装pcKeepComp值
作者（S）----------Author(s)----------
Oscar Flores <a href="mailto flores@mmb.pcb.ub.es">oflores@mmb.pcb.ub.es</a>, David Rosell <a href="mailto:david.rosell@irbbarcelona.org">david.rosell@irbbarcelona.org</a>
举例----------Examples----------
#Load dataset[负载数据集]
data(nucleosome_htseq)
data = as.vector(coverage.rpm(nucleosome_htseq)[[1]])
#Get recommended pcKeepComp value[获得推荐的pcKeepComp价值]
pckeepcomp = pcKeepCompDetect(data, cor.target=0.99)
print(pckeepcomp)
#call filterFFT[调用filterFFT]
f1 = filterFFT(data, pcKeepComp=pckeepcomp)
#Also this can be called directly[这也可以直接调用]
f2 = filterFFT(data, pcKeepComp="auto", cor.target=0.99)
#Plot[图]
plot(data[1:2000], col="black", type="l", lwd=2)
lines(f1[1:2000], col="red", lwd=2)
lines(f2[1:2000], col="blue", lwd=2, lty=2)
legend("bottom", c("original", "two calls", "one call"), col=c("black", "red", "blue"), lty=c(1,1,2), horiz=TRUE, bty="n")
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 07:55:00
