genomewide.lsn.plot: Genome-wide Lesion Plot

In GRIN2: Genomic Random Interval (GRIN)

Genome-wide Lesion Plot

Description

Generates a genome-wide lesion plot displaying all lesion types affecting different chromosomes.

Usage

genomewide.lsn.plot(
  grin.res,
  ordered = FALSE,
  pt.order = NULL,
  lsn.colors = NULL,
  max.log10q = NULL
)

Arguments

grin.res	GRIN results (output from the grin.stats function).
ordered	Logical; if TRUE, patient IDs will be reordered according to the pt.order data frame. If FALSE (default), patient IDs are ordered alphabetically.
pt.order	A data frame with two columns: "ID" (patient identifiers matching those in the lesion data) and "pts.order" (numeric vector specifying the new patient order from 1 to n patients). Only required if ordered = TRUE.
lsn.colors	A named vector of colors assigned to lesion types. If not provided, colors will be automatically assigned using the default.grin.colors function.
max.log10q	Numeric; maximum value for -log10(q-value) used in the plot. Any value greater than max.log10q will be capped at this value in the left panel of the plot.

Details

This function uses genome-wide coordinates (from compute.gw.coordinates) to generate a three-panel plot. The middle panel shows lesions by chromosome across patients. The left panel displays the -log10(q-values) from the GRIN results for each gene, and the right panel shows the number of patients affected at each locus, color-coded by lesion type.

Value

A genome-wide lesion plot consisting of three aligned panels:

• Middle panel: genome-wide lesion map across all chromosomes and patients.

• Left panel: -log10(q-values) of each locus from GRIN results showing Statistical Significance of Lesion Frequencies.

• Right panel: number of affected patients at each locus, colored by lesion category.

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

compute.gw.coordinates

Examples

data(lesion_data)
data(hg38_gene_annotation)
data(hg38_chrom_size)

# Run GRIN analysis
grin.results <- grin.stats(lesion_data,
                           hg38_gene_annotation,
                           hg38_chrom_size)

# Generate genome-wide lesion plot with alphabetical patient ordering
genomewide.plot <- genomewide.lsn.plot(grin.results, max.log10q = 50)

GRIN2 documentation built on June 17, 2025, 9:11 a.m.