GRIN2 (version 2.0.0)

prep.binary.lsn.mtx: 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)

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.

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.

Author

Abdelrahman Elsayed , Stanley Pounds

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.

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)