View source: R/analysis_correlation.R
[.GEandAScorrelation | R Documentation |
Plot, print and display as table the results of gene expression and alternative splicing
## S3 method for class 'GEandAScorrelation'
x[genes = NULL, ASevents = NULL]
## 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
)
## S3 method for class 'GEandAScorrelation'
print(x, ...)
## S3 method for class 'GEandAScorrelation'
as.table(x, pvalueAdjust = "BH", ...)
x |
|
genes |
Character: genes |
ASevents |
Character: AS events |
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
Other functions to correlate gene expression and alternative splicing:
correlateGEandAS()
Other functions to correlate gene expression and alternative splicing:
correlateGEandAS()
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)
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