Create a trackplot to show the association between miRNAs and disease-SNPs

This function plots a trackplot that shows the genomic position of disease-associated SNPs that affect miRNA genes. This is useful to visualize the genomic position and context of disease-associated variants that may affect miRNA expression.

Usage

mirVariantPlot(
  variantId,
  snpAssociation,
  showContext = FALSE,
  showSequence = TRUE,
  snpFill = "lightblue",
  mirFill = "orange",
  from = NULL,
  to = NULL,
  title = NULL,
  ...
)

Arguments

variantId

A valid name of a SNP variant! (e.g. "rs394581")

snpAssociation

A data.frame object containing the results of findMirnaSNPs() function

showContext

Logical, if TRUE a complete genomic context with genes present in the region will be shown. Default is FALSE to just display the variant and the miRNA gene

showSequence

Logical, whether to display a color-coded sequence at the bottom of the trackplot. Default is TRUE. This parameter will be set to FALSE if showContext is TRUE

snpFill

It must be an R color name that specifies the fill color of the SNP locus. Default is lightblue. Available color formats include color names, such as 'blue' and 'red', and hexadecimal colors specified as #RRGGBB

mirFill

It must be an R color name that specifies the fill color of the miRNA locus. Default is orange. Available color formats include color names, such as 'blue' and 'red', and hexadecimal colors specified as #RRGGBB

from

The start position of the plotted genomic range. Default is NULL to automatically determine an appropriate position

to

The end position of the plotted genomic range. Default is NULL to automatically determine an appropriate position

title

The title of the plot. Default is NULL not to include a plot title

...

Other parameters that can be passed to Gviz::plotTracks() function

Value

A trackplot with information about chromosome, SNP and miRNA gene location.

Note

This function retrieves genomic coordinates from the output of findMirnaSNPs() function and then uses Gviz package to build the trackplot.

References

Hahne, F., Ivanek, R. (2016). Visualizing Genomic Data Using Gviz and Bioconductor. In: Mathé, E., Davis, S. (eds) Statistical Genomics. Methods in Molecular Biology, vol 1418. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3578-9_16

Author

Jacopo Ronchi, jacopo.ronchi@unimib.it

Examples

# \donttest{
# load example MirnaExperiment object
obj <- loadExamples()

# retrieve associated SNPs
association <- findMirnaSNPs(obj, "response to antidepressant")
#> Querying GWAS Catalog, this may take some time...
#> Finding genomic information of differentially expressed miRNAs...
#> After the analysis, 1 variants associated with response to antidepressant were found within differentially expressed miRNA genes

# visualize association as a trackplot
mirVariantPlot(variantId = "rs2402960", snpAssociation = association)

# }