Principal component analysis(PCA) for SVA corrected data and raw data — svapca • enviGCMS

Principal component analysis(PCA) for SVA corrected data and raw data

svapca(list, center = TRUE, scale = TRUE, lv = NULL)

Arguments

list: results from svacor function
center: parameters for PCA
scale: parameters for scale
lv: group information

Value

plot

See also

svacor, svaplot, svabatch

Examples

if (FALSE) {
library(faahKO)
cdfpath <- system.file("cdf", package = "faahKO")
cdffiles <- list.files(cdfpath, recursive = TRUE, full.names = TRUE)
xset <- xcmsSet(cdffiles)
xset <- group(xset)
xset2 <- retcor(xset, family = "symmetric", plottype = "mdevden")
xset2 <- group(xset2, bw = 10)
xset3 <- fillPeaks(xset2)
df <- svacor(xset3)
svapca(df)
}