grin.stats: GRIN Statistics Output

In GRIN2: Genomic Random Interval (GRIN)

GRIN Statistics Output

Description

The function run the Genomic Random Interval (GRIN) analysis to determine whether a certain locus has an abundance of lesions or a constellation of multiple types of lesions that is statistically significant.

Usage

grin.stats(lsn.data, gene.data = NULL, chr.size = NULL, genome.version = NULL)

Arguments

lsn.data	data.frame with lesion data prepared by the user in a GRIN compatible format. Object should has five columns that include "ID" with patient ID, "chrom" which is the chromosome on which the lesion is located, "loc.start" which is the lesion start position, "loc.end" the lesion end position and "lsn.type" which is the lesion category for example gain, loss, mutation, fusion, etc... For Single Nucleotide Variants (SNVs), loc.start will be the same as loc.end. For Copy Number Alterations (CNAs) such as gain and deletions, loc.start and loc.end should be the gain or deletion start and end positions respectively. For structural rearrangements such as inversions and translocations, each rearrangement should be coded in two different lines, one line for chromosome A involved in the translocation break-point and the second line for chromosome B break-point. For inversions on the same chromosome, the two lines will include the two breakpoints of the inversion. An example lesion data in a GRIN compatible format can be found at the GRIN2.0 package data folder (lesion.data.rda).
gene.data	data.frame with the gene annotation data either provided by the user or directly retreived from ensembl BioMart database using get.ensembl.annotation function included in the GRIN2.0 library if the genome.version is specified. Object should has four columns "gene" which is the ensembl ID of annotated genes to which the lesion data will be overlapped, "chrom" which is the chromosome on which the gene is located, "loc.start" which is the gene start position, and "loc.end" the gene end position.
chr.size	data.frame with the size of the 22 autosomes, in addition to X and Y chromosomes in base pairs. It should has two columns that include "chrom" with the chromosome number and "size" for the size of the chromosome in base pairs. Chromosome size data can be either provided by the user or directly retreived from UCSC genome browser using get.chrom.length function included in the GRIN2.0 library if genome.version is specified.
genome.version	Genome assembly should be only specified if the user selected not to provide gene annotation, chromosome size files, and directly retrieve those files from ensembl BioMart database, and UCSC genome browsers using get.ensembl.annotation and get.chrom.length functions respectively. Currently, the function support four genome assemblies that include "Human_GRCh38", "Human_GRCh37", "Mouse_HGCm39", and "Mouse_HGCm38".

Details

The function run the Genomic Random Interval (GRIN) analysis and evaluates the probability of each gene locus to be affected by different types of lesions based on a convolution of independent but non-identical Bernoulli distributions to determine whether this locus has an abundance of lesions that is statistically significant.In addition, FDR-adjusted q value is computed for each locus based on Pounds & Cheng (2006) estimator of the proportion of tests with a true null (pi.hat). The function also evaluates if a certain locus is affected by a constellation of multiple types of lesions and return the GRIN results table.

Value

A list with the following components:

gene.hits	data table of GRIN results that include gene annotation, number of subjects affected by each lesion type for example gain, loss, mutation, etc.., and number of hits affecting each locus. The GRIN results table will also include P and FDR adjusted q-values showing the probability of each locus of being affected by one or a constellation of multiple types of lesions.
lsn.data	input lesion data
gene.data	input gene annotation data
gene.lsn.data	each row represent a gene overlapped by a certain lesion. Column "gene" shows the overlapped gene ensembl ID and "ID"" column has the patient ID.
chr.size	data table showing the size of the 22 autosomes, in addition to X and Y chromosomes in base pairs.
gene.index	data.frame with overlapped gene-lesion data rows that belong to each chromosome in the gene.lsn.data table.
lsn.index	data.frame that shows the overlapped gene-lesion data rows taht belong to each lesion in the gene.lsn.data table.

Author(s)

Stanley Pounds [e-mail]

References

Pounds, Stan, 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(), count.hits(), prob.hits()

Examples

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

# if gene annotation and chromosome size files will be provided by the user:
grin.results=grin.stats(lesion.data,
                        hg19.gene.annotation,
                        hg19.chrom.size)

# to directly retrieve gene annotation and chromosome size files from Ensembl BioMart database,
# and UCSC genome browsers using get.ensembl.annotation and get.chrom.length functions respectively,
# users can select to specify certain genome assembly using the 'genome.version' argument:
# "Human_GRCh37" can be used for the GRCH37 (hg19) genome assembly, and "Human_GRCh38" can be used
# for the GRCH38 (hg38) genome assembly

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