GRIN2 (version 2.0.0)

KW.hit.express: Associate Lesion Groups with Gene Expression

Description

Performs the Kruskal Wallis (KW) test to evaluate the association between lesion groups and the expression level of the corresponding gene.

Usage

KW.hit.express(alex.data, gene.annotation, min.grp.size = NULL)

Value

A data frame where each row corresponds to a gene tested. Columns include:

gene

Ensembl gene ID.

gene.name

HGNC gene symbol.

p.KW

Kruskal Wallis test p-value.

q.KW

FDR-adjusted q-value for multiple testing correction.

_n.subjects

Number of subjects in each lesion group, including "none" and "multiple".

_mean

Mean expression per lesion group.

_median

Median expression per lesion group.

_sd

Standard deviation of expression per lesion group.

Arguments

alex.data

Output from the alex.prep.lsn.expr function. A list of three data frames:

• row.mtch: Table of matched lesion expression entries, including gene IDs.

• alex.expr: Gene expression matrix (rows = genes by Ensembl ID, columns = patient IDs).

• alex.lsn: Lesion status matrix with the same dimensions/order as alex.expr.

gene.annotation

Gene annotation table. Must be a data.frame with the following columns: gene (Ensembl gene ID), chrom (chromosome), loc.start (start position), and loc.end (end position). Can be obtained manually or via the get.ensembl.annotation function.

min.grp.size

Minimum number of patients required in a lesion group to be included in the test. For a gene to be tested, there must be at least two groups with more than min.grp.size patients each.

Author

Abdelrahman Elsayed and Stanley Pounds

Details

For each row in the row.mtch table, the function performs a Kruskal Wallis test comparing expression values of the gene across lesion groups. The lesion groups are defined in the alex.lsn matrix. Patients with multiple types of lesions in a gene are assigned the label "multiple", and those with no lesion are labeled "none". The expression values are obtained from the corresponding row in alex.expr.

The function tests whether expression levels significantly differ across lesion groups for the same gene.

References

Hollander, M., & Wolfe, D. A. (1973). Nonparametric Statistical Methods. New York: Wiley. pp. 115-120.

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

See Also

alex.prep.lsn.expr

Examples

data(expr_data)
data(lesion_data)
data(hg38_gene_annotation)

# Prepare matched lesion-expression data
alex.data <- alex.prep.lsn.expr(expr_data, lesion_data,
                                hg38_gene_annotation,
                                min.expr = 1, min.pts.lsn = 5)

# Perform Kruskal Wallis test between lesion groups and expression levels:
alex.kw.results <- KW.hit.express(alex.data,
                                  hg38_gene_annotation,
                                  min.grp.size = 5)