grin.oncoprint.mtx: GRIN OncoPrint Matrix

In GRIN2: Genomic Random Interval (GRIN)

GRIN OncoPrint Matrix

Description

Function use GRIN results table and prepare the lesion matrix that the user can pass to the oncoprint function from ComplexHeatmap package to geneate an OncoPrint for a selcted list of genes.

Usage

grin.oncoprint.mtx(grin.res, oncoprint.genes)

Arguments

grin.res	GRIN results (output of the grin.stats function).
oncoprint.genes	Vector of ensembl IDs for the selected list of genes to be added to the OncoPrint.

Details

Function will use the input list of ensembl IDs to prepare a data table of lesions that affect these genes (each row is a gene and each column is a patient ID). This lesion matrix is compatible and can be passed to oncoprint function in ComplexHeatmap library to prepare an OncoPrint for lesions in the selected list of genes.

Value

Function uses the output results of grin.stats function and return data table of lesions that affect a group of selected genes (each row is a gene and each column is a patient ID).

Author(s)

Abdelrahman Elsayed [e-mail] and Stanley Pounds [e-mail]

References

Cao, X., Elsayed, A. H., & Pounds, S. B. (2023). Statistical Methods Inspired by Challenges in Pediatric Cancer Multi-omics.

See Also

grin.stats()

Examples

data(lesion.data)
data(hg19.gene.annotation)
data(hg19.chrom.size)

# Run GRIN analysis using grin.stats function:
grin.results=grin.stats(lesion.data,
                        hg19.gene.annotation,
                        hg19.chrom.size)

# specify a list of genes to be included in the oncoprint (driver genes):
oncoprint.genes=as.vector(c("ENSG00000148400", "ENSG00000171862", "ENSG00000171843",
                            "ENSG00000156531", "ENSG00000162367", "ENSG00000096968",
                            "ENSG00000105639", "ENSG00000118513","ENSG00000102974",
                            "ENSG00000133703"))

# prepare the oncoprint lesion matrix:
oncoprint.mtx=grin.oncoprint.mtx(grin.results,
                                 oncoprint.genes)

# user can also specify a list of top significant genes in the GRIN constellation test:
# for example: select genes affected by two types of lesion with q2.nsubj<0.01:
genes.const = grin.results$gene.hits[grin.results$gene.hits$q2.nsubj < 0.01, ]
# get ensembl.ids for this list of genes
selected.genes=as.vector(genes.const$gene)
oncoprint.mtx.const=grin.oncoprint.mtx(grin.results,
                                       selected.genes)

GRIN2 documentation built on April 4, 2025, 1:41 a.m.