clusterGenome(aCGH)
clusterGenome()所属R语言包：aCGH
clustering and heatmap
聚类和热图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function clusters samples and shows their heatmap
此功能聚类样本，并显示其热图
用法----------Usage----------
clusterGenome(aCGH.obj,
response = as.factor(rep("All", ncol(aCGH.obj))),
chrominfo = human.chrom.info.Jul03, cutoff=1,
lowCol = "red", highCol = "green", midCol = "black",
ncolors = 50, byclass = FALSE, showaber = FALSE,
amplif = 1, homdel = -0.75,
samplenames = sample.names(aCGH.obj),
vecchrom = 1:23, titles = "Image Plot",
methodS = "ward", dendPlot = TRUE, imp = TRUE,
categoricalPheno = TRUE)
参数----------Arguments----------
参数：aCGH.obj
object of class aCGH here
对象类aCGH这里
参数：response
phenotype of interest. defaults to the same phenotype assigned to all samples
表型的利益。默认分配给所有样品相同的表型
参数：chrominfo
a chromosomal information associated with the mapping of the data
染色体相关的信息与数据的映射
参数：cutoff
maximum absolute value. all the values are floored to +/-cutoff depending on whether they are positive of negative. defaults to 1
最大绝对值。所有值都取决于他们是否是积极的负+ /截止地板。默认为1
参数：ncolors
number of colors in the grid. input to maPalette. defaults to 50
在网格中的颜色数。输入maPalette的。默认为50
参数：lowCol
color for the low (negative) values. input to maPalette. defaults to "red"
颜色为低（负）值。输入maPalette的。默认为“红”
参数：highCol
color for the high (positive) values. input to maPalette. defaults to "green"
颜色为高（正）值。输入maPalette的。默认为“绿色”
参数：midCol
color for the values close to 0. input to maPalette. defaults to "black"
色值接近0。输入maPalette的。默认为“黑”
参数：byclass
logical indicating whether samples should be clustered within each level of the phenotype or overall. defaults to F
逻辑说明样品是否应在各型或整体水平的聚集。默认为F
参数：showaber
logical indicating whether high level amplifications and homozygous deletions should be indicated on the plot. defaults to F
逻辑说明是否应积表示，高水平的扩增和纯合性缺失。默认为F
参数：amplif
positive value that all observations equal or exceeding it are marked by yellow dots indicating high-level changes. defaults to 1
正面价值等于或超过它的所有意见都表明高层变动的黄点标记。默认为1
参数：homdel
negative value that all observations equal or below it are marked by light blue dots indicating homozygous deletions. defaults to -0.75
负值，所有观测值等于或低于它表明纯合性缺失的淡蓝色圆点标记。默认以-0.75
参数：samplenames
sample names
样品名称
参数：vecchrom
vector of chromosomal indeces to use for clustering and to display. defaults to 1:23
染色体indeces向量使用聚类和显示。默认以1:23
参数：titles
plot title. defaults to "Image Plots"
小区称号。默认“影像显示”
参数：methodS
clustering method to cluster samples. defaults to "ward"
聚类样本聚类方法。默认为“病房”
参数：dendPlot
logical indicating whether dendogram needs to be drawn. defaults to T.
逻辑说明是否需要绘制dendogram。默认为T
参数：imp
logical indicating whether imputed or original values should be used. defaults to T, i.e. imputed.
逻辑表明，是否应采用估算或原始值。默认为T，即估算。
参数：categoricalPheno
logical indicating whether phenotype is categorical. Continious phenotypes are treated as "no groups" except that their values are dispalyed.defaults to TRUE.
逻辑说明是否是分类型。被视为“无群体”，除了他们的价值观是为TRUE dispalyed.defaults 305.11表型。
Details
详情----------Details----------
This functions is a more flexible version of the heatmap. It can cluster within levels of categorical phenotype as well as all of the samples while displaying phenotype levels in different colors. It also uses any combination of chromosomes that is requested and clusters samples based on these chromosomes only. It draws the chromosomal boundaries and displays high level changes and homozygous deletions. If phenotype if not categical, its values may still be displayed but groups are not formed and byclass = F. Image plot has the samples reordered according to clustering order.
这个功能是一个更灵活的版本heatmap。它可以同时显示不同颜色的表型水平，分类型的水平，以及聚类内所有的样本。它还使用任何要求和聚类样品，只有在这些染色体的染色体组合。它绘制染色体的界限，并显示了较高水平的变化和纯合性缺失。如果表型的如果不categical的，其价值可能仍然可以显示，但没有形成群体和byclass = F图像图的样本重新排序根据聚类秩序的。
参见----------See Also----------
aCGH heatmap
aCGHheatmap
举例----------Examples----------
data(colorectal)
#cluster all samples using imputed data on all chromosomes (autosomes and X):[聚类中的所有样品上使用的所有染色体（常染色体和X）的估算数据：]
clusterGenome(colorectal)
#cluster samples within sex groups based on 3 chromosomes individually. [基于3染色体个别性别组别内的聚类样品。]
#use non-imputed data and do not show dendogram. Indicate amplifications and [使用非估算数据和不显示dendogram。表明扩增和]
#homozygous deletions.[纯合性缺失。]
clusterGenome(colorectal, response = phenotype(colorectal)$sex,
byclass = TRUE, showaber = TRUE, vecchrom = c(4,8,9),
dendPlot = FALSE, imp = FALSE)
#cluster samples based on each chromosome individualy and display age. Show[根据每个的染色体individualy和显示年龄聚类样本。显示]
#gains in red and losses in green. Show aberrations and use values < -1[红色和绿色的损失的收益。畸变和使用价值<-1]
#to identify homozgous deletions. Do not show dendogram.[确定homozgous缺失。不显示dendogram。]
pdf("plotimages.pdf", width = 11, height = 8.5)
for (i in 1:23)
clusterGenome(colorectal,
response = phenotype(colorectal)$age,
chrominfo = human.chrom.info.Jul03,
cutoff = 1, ncolors = 50, lowCol="green",
highCol="red", midCol="black", byclass = FALSE,
showaber = TRUE, homdel = -1, vecchrom = i,
titles = "Image Plot", methodS = "ward",
dendPlot = FALSE, categoricalPheno = FALSE)
dev.off()
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 10:58:42
