sumstats: Summary statistics on xy co-ordinates, returns the slopes and...
In SamGG/made4: Multivariate analysis of microarray data using ADE4

Description Usage Arguments Details Value Author(s) Examples

Given a data.frame or matrix containing xy coordinates, it returns the slope and distance from origin of each coordinate.

1	sumstats(array, xax = 1, yax = 2)

`array`	A `data.frame` or `matrix` containing xy coordinates, normally a \$co, \$li from `dudi` such as PCA or COA, or \$ls from `bga`
`xax`	Numeric, an integer indicating the column of the x axis coordinates. Default xax=1
`yax`	Numeric, an integer indicating the column of the x axis coordinates. Default xax=2

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.

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.

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.

A matrix (ncol=3) containing

1
2
3

   slope 
   angle (in degrees) 
   distance from origin

of each x,y coordinates in a matrix.

Aedin Culhane

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
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
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)