plot.GEandAScorrelation {psichomics} | R Documentation |
Display results of correlation analyses
## S3 method for class 'GEandAScorrelation' plot(x, autoZoom = FALSE, loessSmooth = TRUE, loessFamily = c("gaussian", "symmetric"), colour = "black", alpha = 0.2, size = 1.5, loessColour = "red", loessAlpha = 1, loessWidth = 0.5, fontSize = 12, ..., colourGroups = NULL, legend = FALSE, showAllData = TRUE, density = FALSE, densityColour = "blue", densityWidth = 0.5) plotCorrelation(x, autoZoom = FALSE, loessSmooth = TRUE, loessFamily = c("gaussian", "symmetric"), colour = "black", alpha = 0.2, size = 1.5, loessColour = "red", loessAlpha = 1, loessWidth = 0.5, fontSize = 12, ..., colourGroups = NULL, legend = FALSE, showAllData = TRUE, density = FALSE, densityColour = "blue", densityWidth = 0.5) ## S3 method for class 'GEandAScorrelation' print(x, ...) ## S3 method for class 'GEandAScorrelation' as.table(x, pvalueAdjust = "BH", ...)
x |
|
autoZoom |
Boolean: automatically set the range of PSI values based on
available data? If |
loessSmooth |
Boolean: plot a smooth curve computed by
|
loessFamily |
Character: if |
colour |
Character: points' colour |
alpha |
Numeric: points' alpha |
size |
Numeric: points' size |
loessColour |
Character: loess line's colour |
loessAlpha |
Numeric: loess line's opacity |
loessWidth |
Numeric: loess line's width |
fontSize |
Numeric: plot font size |
... |
Arguments passed on to
|
colourGroups |
List of characters: sample colouring by group |
legend |
Boolean: show legend for sample colouring? |
showAllData |
Boolean: show data outside selected groups as a single
group (coloured based on the |
density |
Boolean: contour plot of a density estimate |
densityColour |
Character: line colour of contours |
densityWidth |
Numeric: line width of contours |
pvalueAdjust |
Character: method used to adjust p-values (see Details) |
The following methods for p-value adjustment are supported by using the
respective string in the pvalueAdjust
argument:
none
: do not adjust p-values
BH
: Benjamini-Hochberg's method (false discovery rate)
BY
: Benjamini-Yekutieli's method (false discovery rate)
bonferroni
: Bonferroni correction (family-wise error rate)
holm
: Holm's method (family-wise error rate)
hochberg
: Hochberg's method (family-wise error rate)
hommel
: Hommel's method (family-wise error rate)
Plots, summary tables or results of correlation analyses
annot <- readFile("ex_splicing_annotation.RDS") junctionQuant <- readFile("ex_junctionQuant.RDS") psi <- quantifySplicing(annot, junctionQuant, eventType=c("SE", "MXE")) geneExpr <- readFile("ex_gene_expression.RDS") corr <- correlateGEandAS(geneExpr, psi, "ALDOA") # Quick display of the correlation results per splicing event and gene print(corr) # Table summarising the correlation analysis results as.table(corr) # Correlation analysis plots colourGroups <- list(Normal=paste("Normal", 1:3), Tumour=paste("Cancer", 1:3)) attr(colourGroups, "Colour") <- c(Normal="#00C65A", Tumour="#EEE273") plot(corr, colourGroups=colourGroups, alpha=1)