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R语言 spclust包 spclust2()函数中文帮助文档(中英文对照)

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发表于 2012-9-30 14:28:41 | 显示全部楼层 |阅读模式
spclust2(spclust)
spclust2()所属R语言包:spclust

                                        Perform multi-stage selective phenotyping clustering
                                         执行多级选择的表型聚类

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

This function performs a second stage of selective phenotyping clustering where the second stage may aim to maximize diversity in regions of the genome highlighted in results from the first stage of phenotyping. The plot function plots the clusters from spclust2 with some summary information. For hierarchical clustering methods the dendrogram is displayed with clusters and individuals selected in each stage are marked. Graphical genotypes are displayed for individuals selected with maximal recombinations.
执行该功能的选择性表型聚类的第二阶段,在第二阶段可能旨在最大限度地在突出显示在结果中,从第一阶段的表型的基因组的区域的多样性。绘图功能画出了聚类spclust2的一些摘要信息。对于层次聚类方法显示树状图,聚类和个人在每个阶段中选择的标记。图形显示基因型的个人选择最大的重组。


用法----------Usage----------


spclust2 (object, spobj, ss2, file, method=c("stage1", "maxrec"), step=5, threshold=.7)
## S3 method for class 'spclust2'
plot(x, ...)
## S3 method for class 'spclust2'
print(x, ...)
## S3 method for class 'spclust2'
summary(object, ...)



参数----------Arguments----------

参数:object
Cross or mpcross object containing genetic data; for summary function, spclust object
,红十字会或mpcross反对基因数据的汇总函数,spclust对象


参数:x
spclust object input to plot function
spclust对象输入到绘图功能


参数:spobj
spclust object with output from the first stage of SPCLUST
从第一阶段SPCLUST spclust对象输出


参数:ss2
Sample size to be selected in second stage
在第二阶段中选择的样本大小


参数:file
Optional argument, filename for outputting clusters to a file
可选参数,输出聚类,一个文件的文件名


参数:method
Selection method in second stage - may either match that in first stage or use maximum recombinations
在第二个阶段 - 选择方法可以比拟的,在第一阶段或使用最大重组


参数:step
Step size used in estimating recombinations (default=5 cM)
步长,估计重组(默认值= 5厘米)


参数:threshold
Threshold used in estimating recombinations (default=0.7)
阈值估计重组(默认值= 0.7)


参数:...
Additional arguments to be passed on to plot functions
其他参数被传递到绘图功能


值----------Value----------

list with components:
组件列表:


参数:stage1
Input spclust object containing stage 1 selections  <tr valign="top"><td>stage2</td>
的输入spclust对象,其中包含阶段1选择<tr valign="top"> <TD>stage2</ TD>

spclust object containing stage 2 selections
spclust对象,其中包含2阶段的选择


参数:lines
indices of selected lines from both stages
指标的选定行的两个阶段


参数:mind
For each selected line, minimum distance to other lines in sample  <tr valign="top"><td>tree</td>
对于每个选定的线,最小距离,以样品中的其它线路<tr valign="top"> <TD>tree</运输署>

Hierarchical clustering tree  <tr valign="top"><td>clusters</td>
分层聚类树<tr valign="top"> <TD> clusters</ TD>

Assignment of all lines to clusters
分配到聚类中的所有行


注意----------Note----------

Stage 2 SPCLUST performs the following steps in order to select a second stage of selected lines with high genetic diversity after accounting for the originally selected lines. First, genetic distances are estimated between all lines in the sample, based on the expected proportion of alleles not shared IBD across the genome. Second, if the "maxrec" method is selected, ss2 lines are selected with the highest number of estimated recombinations, excluding those which have already been selected in the first stage. Otherwise, all lines are clustered based on the genetic distance, with the number of clusters equal to the sum of sample sizes indicated for selection in stages 1 and 2. All lines selected in stage 1 are included in the final sample, and clusters containing these lines are excluded from further selection. From ss2 of the remaining clusters, a representative is selected as the one most similar to other lines in the cluster.
第2阶段SPCLUST执行以下步骤,以选择第二个阶段,最初选定的行会计处理后,具有较高的遗传多样性选择的行。首先,遗传距离估计样品中的所有行之间,基于预期的比例不共享IBD在整个基因组的等位基因。其次,如果“maxrec”的方法选择,β2的线选择具有最高编号的估计重组,但不包括那些已经在第一阶段中选择的。否则,所有的线路都聚集的遗传距离的基础上,与在阶段1和2中表示的选择的簇的数目等于样本大小的总和。在第1阶段中选择的所有线都包含在最终的样品,和包含这些行的聚类被排除在进一步选择的。从β2的剩余的簇,一个代表被选择作为一个最类似的聚类中的其他行。


参见----------See Also----------

spdist, plot.spclust, spclust, plclust_in_colour
spdist,plot.spclust,spclust,plclust_in_colour


实例----------Examples----------


# Simulate a map and data using qtl package[模拟图和数据使用的QTL包。]
map <- sim.map(len=rep(100, 5), n.mar=21, eq.spacing=TRUE, include.x=FALSE)
dat <- sim.cross(map, n.ind=500, type="f2")
# Select two samples of size 100 in two stages[选择两个样本大小为100分两个阶段进行]
sp <- spclust(dat, 100, method="ward")
sp2 <- spclust2(dat, sp, 100, method="stage1")
summary(sp2)
plot(sp2)

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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