sumstats(made4)
sumstats()所属R语言包:made4
Summary statistics on xy co-ordinates, returns the slopes and distance from origin of each co-ordinate.
汇总统计上的XY坐标,返回从各统筹原产地的坡度和距离。
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Given a data.frame or matrix containing xy coordinates, it returns the slope and distance from origin of each coordinate.
data.frame或matrix含有XY坐标,它返回的斜坡和每个坐标原点的距离。
用法----------Usage----------
sumstats(array, xax = 1, yax = 2)
参数----------Arguments----------
参数:array
A data.frame or matrix containing xy coordinates, normally a \$co, \$li from dudi such as PCA or COA, or \$ls from bga
一个data.frame或matrixxy坐标,通常是\ $合作,\ $dudi如PCA或农委会,或\ $ LS李从bga
参数:xax
Numeric, an integer indicating the column of the x axis coordinates. Default xax=1
数字,一个整数,指示列的X轴坐标。默认XAX = 1
参数:yax
Numeric, an integer indicating the column of the x axis coordinates. Default xax=2
数字,一个整数,指示列的X轴坐标。默认XAX = 2
Details
详情----------Details----------
In PCA or COA, the variables (upregulated genes) that are most associated with a case (microarray sample), are those that are projected in the same direction from the origin.
在PCA或农委会,(上调基因),大多数情况下(芯片样品)关联的变量,是那些预计在同一方向从源头。
Variables or cases that have a greater contribution to the variance in the data are projected further from the origin in PCA. Equally variables and cases with the strong association have a high chi-square value, and are projected with greater distance from the origin in COA, See a description from Culhane et al., 2002 for more details.
进一步变量或有更大的贡献,在数据的方差的情况下,预计在PCA的起源。同样具有很强的关联变量和情况具有较高的卡方值,并预计在农委会的起源与更大的距离,从Culhane等人,2002年更多的细节描述。
Although the projection of co-ordinates are best visualised on an xy plot, sumstats returns the slope and distance from origin of each x,y coordinate in a matrix.
虽然是最好的一个XY图上可视化统筹投影,sumstats返回原籍每个x坡度和距离,y坐标矩阵。
值----------Value----------
A matrix (ncol=3) containing
矩阵(NCOL = 3),其中包含
作者(S)----------Author(s)----------
Aedin Culhane
举例----------Examples----------
data(khan)
if (require(ade4, quiet = TRUE)) {
khan.bga<-bga(khan$train, khan$train.classes)}
plotarrays(khan.bga$bet$ls, classvec=khan$train.classes)
st.out<-sumstats(khan.bga$bet$ls)
# Get stats on classes EWS and BL[获取类预警系统和“基本法”的统计]
EWS<-khan$train.classes==levels(khan$train.classes)[1]
st.out[EWS,]
BL<-khan$train.classes==levels(khan$train.classes)[2]
st.out[BL,]
# Add dashed line to plot to highlight min and max slopes of class BL[添加虚线绘制类BL突出的最小和最大的斜坡]
slope.BL.min<-min(st.out[BL,1])
slope.BL.max<-max(st.out[BL,1])
abline(c(0,slope.BL.min), col="red", lty=5)
abline(c(0,slope.BL.max), col="red", lty=5)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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