GRIN2 (version 2.0.0)

find.gene.lsn.overlaps: Find Gene Lesion Overlaps

Description

Identifies overlaps between genes and genomic lesions using the output from the prep.gene.lsn.data() function. This function detects all instances where a lesion spans or intersects the genomic coordinates of a gene.

Usage

find.gene.lsn.overlaps(gl.data)

Value

A list containing the following components:

lsn.data

Original input lesion data.

gene.data

Original input gene annotation data.

gene.lsn.data

A data.frame ordered by chromosome and start position, containing both gene and lesion entries. Each row includes a cty code indicating the type and boundary of the interval: 1 = gene start, 2 = lesion start, 3 = lesion end, 4 = gene end.

gene.lsn.hits

A data.frame where each row corresponds to a gene overlapped by a lesion. Includes 11 columns: "gene" (Ensembl gene ID), "gene.chrom", "gene.loc.start", "gene.loc.end" (chromosome and coordinates of the gene), "ID" (patient/sample ID), "lsn.chrom", "lsn.loc.start", "lsn.loc.end" (chromosome and coordinates of the lesion), and "lsn.type" (type of lesion).

gene.index

A data.frame indexing the rows in gene.lsn.data that correspond to each chromosome's genes (row start and row end per chromosome).

lsn.index

A data.frame indexing the rows in gene.lsn.data that correspond to each lesion (row start and row end per lesion).

Arguments

gl.data

A list of five data.frame objects returned by the prep.gene.lsn.data() function. These include processed and indexed gene and lesion data ready for overlap analysis.

Author

Abdelrahman Elsayed , Stanley Pounds

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

Examples

data(lesion_data)
data(hg38_gene_annotation)

# Prepare gene and lesion data for GRIN-based computations:
prep.gene.lsn <- prep.gene.lsn.data(lesion_data, hg38_gene_annotation)

# Identify genes that are overlapped by lesions:
gene.lsn.overlap <- find.gene.lsn.overlaps(prep.gene.lsn)