r bead.data@fcs.filename

Bead Stats

    K <- dim(bead.data@beads.mef)[1]+1
    for (p in names(bead.data@mef.transform)) {
        d <- data.frame(bead.data@clustering.stats[,p, 1:K])
        names(d) <- paste(p, 1:K)
        print(xtable(d), type='html')
     }

Plot

    plot(bead.data)

Regression Summary

    print( xtable(bead.data@mef.transform$APC$m), type='html' )

Flow Cytometer Settings

    print( xtable(t(data.frame(bead.data@description)[1,])), type='html' )


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flowBeads documentation built on Nov. 8, 2020, 5:01 p.m.