plotRowStats {psichomics} | R Documentation |
Plot sample statistics per row
plotRowStats( data, x, y, subset = NULL, xmin = NULL, xmax = NULL, ymin = NULL, ymax = NULL, xlim = NULL, ylim = NULL )
data |
Data frame or matrix |
x, y |
Character: statistic to calculate and display in the plot per row;
choose between |
subset |
Boolean or integer: |
xmin, xmax, ymin, ymax |
Numeric: minimum and maximum X and Y values to draw in the plot |
xlim, ylim |
Numeric: X and Y axis range |
Plot of data
Other functions for gene expression pre-processing:
convertGeneIdentifiers()
,
filterGeneExpr()
,
normaliseGeneExpression()
,
plotGeneExprPerSample()
Other functions for PSI quantification:
filterPSI()
,
getSplicingEventTypes()
,
listSplicingAnnotations()
,
loadAnnotation()
,
quantifySplicing()
library(ggplot2) # Plotting gene expression data geneExpr <- readFile("ex_gene_expression.RDS") plotRowStats(geneExpr, "mean", "var^(1/4)") + ggtitle("Mean-variance plot") + labs(y="Square Root of the Standard Deviation") # Plotting alternative splicing quantification annot <- readFile("ex_splicing_annotation.RDS") junctionQuant <- readFile("ex_junctionQuant.RDS") psi <- quantifySplicing(annot, junctionQuant, eventType=c("SE", "MXE")) medianVar <- plotRowStats(psi, x="median", y="var", xlim=c(0, 1)) + labs(x="Median PSI", y="PSI variance") medianVar rangeVar <- plotRowStats(psi, x="range", y="log10(var)", xlim=c(0, 1)) + labs(x="PSI range", y="log10(PSI variance)") rangeVar