Construct an MA (mean-difference) plot
plotMeanDiff.Rd
Construct an MA (mean-difference) plot
Usage
plotMeanDiff(
res,
meanCol = NULL,
logFCCol = NULL,
pvalCol = NULL,
padjCol = NULL,
padjThreshold = 0.05,
pointSize = "small",
interactivePlot = FALSE,
nTopToLabel = 0
)
Arguments
- res
data.frame
(typically output fromcalculateRelativeFC()
) with columns corresponding to the average abundance (logCPM
orAveExpr
), log-fold change (logFC
) and significance (FDR
oradj.P.Val
).- meanCol, logFCCol, pvalCol, padjCol
Character scalars indicating the columns from
res
that will be used to represent the mean value (x-axis), logFC (y-axis), nominal p-value (used to find the top features to label) and adjusted p-value (used for coloring). IfNULL
(default), pre-specified values will be used depending on the available columns ("logCPM"
or"AveExpr"
,"logFC"
,"PValue"
or"P.Value"
, and"FDR"
or"adj.P.Val"
, respectively).- padjThreshold
Numeric scalar indicating the adjusted p-value threshold to use for coloring the points. All features with adjusted p-value below the treshold will be shown in red.
- pointSize
Either
"small"
or"large"
, indicating which of the two available plot styles that will be used.- interactivePlot
Logical scalar, indicating whether an interactive plot should be returned, in which one can hover over the individual points and obtain further information.
- nTopToLabel
Numeric scalar, indicating the number of points that should be labeled in the plot. The points will be ranked by the
pvalCol
column, and the topnTopToLabel
values will be labeled by the corresponding row names. Only used ifinteractivePlot
isFALSE
.
Examples
se <- readRDS(system.file("extdata", "GSE102901_cis_se.rds",
package = "mutscan"))[1:200, ]
design <- model.matrix(~ Replicate + Condition,
data = SummarizedExperiment::colData(se))
res <- calculateRelativeFC(se, design, coef = "Conditioncis_output")
plotMeanDiff(res, pointSize = "large", nTopToLabel = 3)