cmds(htSeqTools)
cmds()所属R语言包：htSeqTools
Classical Multi-Dimensional Scaling
经典的多维尺度
译者：生物统计家园网 机器人LoveR
描述----------Description----------
cmds obtain the coordinates of the elements in x in a k dimensional space which best approximate the distances between objects. For high-throughput sequencing data we define the distance between two samples as 1 - correlation between their respective coverages. This provides PCA analog for sequencing data.
cmds获取元素的坐标xk三维空间中最佳逼近的物体之间的距离。对于高通量测序数据，我们定义两个样品之间的距离为1 - 之间各自覆盖范围内的相关性。这提供PCA测序数据模拟。
用法----------Usage----------
cmds(x, k=2, logscale=TRUE, mc.cores=1, cor.method='pearson')
参数----------Arguments----------
参数：x
A RangedDataList object, e.g. each element containing the output of a sequencing run.
一个RangedDataList对象，例如每个元素包含的测序运行的输出。
参数：k
Dimensionality of the reconstructed space, typically set to 2 or 3.
重建的空间维度，通常设置为2或3。
参数：logscale
If set to TRUE correlations are computed for log(x+1).
如果设置相关TRUE计算log(x+1)的。
参数：mc.cores
Number of cores. Setting mc.cores>1 allows running computations in parallel. Setting mc.cores to too large a value may require a lot of memory.
芯数。设置mc.cores>1允许运行在并行计算。设置mc.cores值过大，可能需要大量的内存。
参数：cor.method
A character string indicating which correlation coefficient (or covariance) is to be computed. One of "pearson" (default), "kendall", or "spearman", can be abbreviated.
要计算一个字符串，指示哪些相关系数（或协方差）。 “皮尔森”（默认），“肯德尔”，或“矛”，都可以缩写。
值----------Value----------
The function returns a mdsFit object, with slots points containing the coordinates, d with the distances between elements, dapprox with the distances between objects in the approximated space, and R.square indicating the percentage of variability in d accounted for by dapprox.
该函数返回一个mdsFit对象，插槽points包含的坐标，d元素之间的距离，dapprox近似空间中的对象之间的距离， R.square说明d变异的比例占dapprox。
Since the coverage distribution is typically highly asymetric, setting logscale=TRUE reduces the influence of the highest coverage regions in the distance computation, as this is based on the Pearson correlation coefficient.
由于覆盖面的分布通常是高度asymetric设置logscale=TRUE减少距离计算覆盖率最高的区域的影响，因为这是Pearson相关系数为基础的。
方法----------Methods----------
signature(x = "RangedDataList") Use Classical Multi-Dimensional Scaling to plot each element of the RangedDataList object in a k-dimensional space. The coverage is computed for each element in x, and the pairwise correlations
signature(x = "RangedDataList")使用古典的多维尺度绘制一个k-维空间中的RangedDataList对象中的每个元素。每个元素的覆盖率计算x，和成对相关
举例----------Examples----------
data(htSample)
cmds1 <- cmds(htSample)
cmds1
plot(cmds1)
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 22:01:02
