prep.binary.lsn.mtx: Prepare Binary Lesion Matrix

In GRIN2: Genomic Random Interval (GRIN)

Prepare Binary Lesion Matrix

Description

Constructs a binary matrix representing the presence or absence of specific lesion types affecting individual genes across patients. Each row corresponds to a gene-lesion type combination, and each column corresponds to a patient.

Usage

prep.binary.lsn.mtx(ov.data, min.ngrp = 0)

Arguments

ov.data	A list of six data.frame objects representing the output from the find.gene.lsn.overlaps function.
min.ngrp	Optional integer specifying the minimum number of patients that must be affected by a given gene-lesion combination to be retained in the output matrix. The default is 0, which includes all combinations affecting at least one patient.

Details

The function processes the overlap results from find.gene.lsn.overlaps and constructs a binary matrix with dimensions: (gene and lesion type) by patient.

Each row is labeled using the format <gene.ID>_<lesion.type> (e.g., ENSG00000118513_gain for a gain affecting the MYB gene). For each gene-lesion combination, a patient receives a value of 1 if affected by that specific lesion type in the corresponding gene, and 0 otherwise.

Rows representing rare lesions (i.e., affecting fewer patients than min.ngrp) are excluded from the final matrix if min.ngrp > 0.

Value

A binary matrix (as a data.frame) where:

• Rows correspond to gene-lesion combinations (gene.ID_lesion.type).

• Columns correspond to patient IDs.

• Entries are binary: 1 if the patient is affected by such a specific type of lesion in that gene, 0 otherwise.

Author(s)

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

References

Pounds, S., et al. (2013). A genomic random interval model for statistical analysis of genomic lesion data.

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

See Also

prep.gene.lsn.data, find.gene.lsn.overlaps

Examples

data(lesion_data)
data(hg38_gene_annotation)

# 1) Prepare gene-lesion input data:
prep.gene.lsn <- prep.gene.lsn.data(lesion_data,
                                    hg38_gene_annotation)

# 2) Identify gene-lesion overlaps:
gene.lsn.overlap <- find.gene.lsn.overlaps(prep.gene.lsn)

# 3) Create binary lesion matrix including only lesion-gene pairs affecting >= 5 patients:
lsn.binary.mtx <- prep.binary.lsn.mtx(gene.lsn.overlap, min.ngrp = 5)

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