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Correlate gene expression data against alternative splicing quantification

Source: R/analysis_correlation.R
correlateGEandAS.Rd

Test for association between paired samples' gene expression (for any genes of interest) and alternative splicing quantification.

Usage

correlateGEandAS(geneExpr, psi, gene, ASevents = NULL, ...)

Arguments

geneExpr

Matrix or data frame: gene expression data

psi

Matrix or data frame: alternative splicing quantification data

gene

Character: gene symbol for genes of interest

ASevents

Character: alternative splicing events to correlate with gene expression of a gene (if NULL, the events will be automatically retrieved from the given gene)

...

Extra parameters passed to cor.test

Value

List of correlations where each element contains:

eventID

Alternative splicing event identifier

cor

Correlation between gene expression and alternative splicing quantification of one alternative splicing event

geneExpr

Gene expression for the selected gene

psi

Alternative splicing quantification for the alternative splicing event

See also

Other functions to correlate gene expression and alternative splicing: [.GEandAScorrelation()

Examples

annot <- readFile("ex_splicing_annotation.RDS")
junctionQuant <- readFile("ex_junctionQuant.RDS")
psi <- quantifySplicing(annot, junctionQuant, eventType=c("SE", "MXE"))
#> Using 3 of 3 events (100%) whose junctions are present in junction quantification data...
#>   |                                        |   0% 
  |========                                |  20% 
  |================                        |  40% 
  |========================                |  60% 
  |================================        |  80% 
  |========================================| 100% 

#> Using 3 of 3 events (100%) whose junctions are present in junction quantification data...
#>   |                                        |   0% 
  |========                                |  20% 
  |================                        |  40% 
  |========================                |  60% 
  |================================        |  80% 
  |========================================| 100% 


geneExpr <- readFile("ex_gene_expression.RDS")
correlateGEandAS(geneExpr, psi, "ALDOA")
#> ================================================================================
#> SE_2_+_32_35_37_38_ALDOA splicing event
#> ALDOA|226 gene expression
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  exprNum and eventPSInum
#> t = -0.7542, df = 4, p-value = 0.4927
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.9051981  0.6427793
#> sample estimates:
#>        cor 
#> -0.3528456 
#> 
#> ================================================================================
#> MXE_2_+_32_35_37_38_40_42_ALDOA splicing event
#> ALDOA|226 gene expression
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  exprNum and eventPSInum
#> t = -0.26642, df = 4, p-value = 0.8031
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.8522745  0.7610748
#> sample estimates:
#>        cor 
#> -0.1320457 
#>