Description Usage Arguments Value Examples
Mark outlying expressions on the scatter plot of a given marker
1 2 3 4 |
dat |
an object of log2-normalized protein (or gene) expressions, containing markers in rows and samples in columns. |
dat.imp |
the imputed data that putatively represents the expressions of the markers in the (matched) normal states. |
dat.imp.test |
marker's p-value of the statistical significance between its observed vs imputed values computed by the Kolmogorov-Smirnov test. |
dat.dys |
samples' distances to regression line (i.e., dysregulation) on the scatter plots. |
dys.sig.thr.upp |
the dysregulation score threshold to elucidate/mark significantly dysregulated outlier events. |
marker.proc.list |
character array, the row names of the data to be processed for outlier analyses and for plotting. |
dataset |
the cohort name to be used in the output files. |
num.omit.fit |
number of outlying events to ignore when fitting a marker's observed expressions to the imputed ones. |
draw.sc |
logical, to draw a scatter plot for every marker in marker.proc.list in a separate PDF file. |
draw.vi |
logical, to draw a violin plot for every marker in marker.proc.list in a separate PDF file. |
conf.int |
confidence interval to display around the regression line |
ylab |
a title for the y axis |
xlab |
a title for the x axis |
the scatter plots of the markers where the outlier dysregulation events are highlighted by red mark.
1 2 3 4 5 6 7 | set.seed(1)
dat = setNames(as.data.frame(matrix(runif(10*10),10,10),
row.names = paste('marker',1:10,sep='')), paste('sample',1:10,sep=''))
dat.imp = artImpute(dat, ku=6)
dat.imp.test = statTest(dat, dat.imp)[[1]]
dat.dys = dysReg(dat, dat.imp)[[1]]
plots = markOut(dat, dat.imp, dat.imp.test, dat.dys, dys.sig.thr.upp = .25)
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