Linear-model interaction test for Tsallis entropy For each gene, fit a linear model of the form `entropy ~ q * group` and extract the p-value for the interaction term (whether the effect of `q` differs between groups). The function expects a `SummarizedExperiment` produced by `calculate_diversity()` when multiple `q` values have been computed (column names contain `_q=`).

Linear-model interaction test for Tsallis entropy For each gene, fit a linear model of the form `entropy ~ q * group` and extract the p-value for the interaction term (whether the effect of `q` differs between groups). The function expects a `SummarizedExperiment` produced by `calculate_diversity()` when multiple `q` values have been computed (column names contain `_q=`).

Usage

calculate_lm_interaction(
  se,
  sample_type_col = NULL,
  min_obs = 10,
  method = c("linear", "lmm", "gam", "fpca"),
  pvalue = c("satterthwaite", "lrt", "both"),
  subject_col = NULL,
  paired = FALSE,
  nthreads = 1,
  assay_name = "diversity",
  verbose = FALSE
)

Arguments

se

A `SummarizedExperiment` containing a `diversity` assay produced by `calculate_diversity(..., q = <vector>)`.

sample_type_col

Optional column name in `colData(se)` that contains a grouping factor for samples (character). If `NULL`, the function will attempt to infer group from column names (suffix `_N` interpreted as 'Normal').

min_obs

Minimum number of non-NA observations required to fit a model for a gene (default: 10).

method

Modeling method to use for interaction testing: one of c('linear', 'lmm', 'gam', 'fpca') (default: 'linear').

pvalue

Type of p-value to compute for linear mixed models: one of c('satterthwaite', 'lrt', 'both') (default: 'satterthwaite').

subject_col

Optional column name in `colData(se)` that contains subject/individual identifiers for paired or repeated-measures designs (character). If provided with `method = 'lmm'`, used as random effect.

paired

Logical; whether samples are paired (default: FALSE).

nthreads

Number of threads (mc.cores) to use for parallel processing (default: 1).

assay_name

Name of the assay in the SummarizedExperiment to use (default: 'diversity').

verbose

Logical; whether to print progress messages during execution (default: FALSE).

Value

A data.frame with columns `gene`, `p_interaction`, and `adj_p_interaction`, ordered by ascending `p_interaction`.

Examples

data('tcga_brca_luma', package = 'TSENAT')
rc <- as.matrix(tcga_brca_luma[1:20, -1, drop = FALSE])
gs <- tcga_brca_luma[1:20, 1]
se <- calculate_diversity(rc, gs, q = c(0.1, 1), norm = TRUE)
# Provide a minimal sample-type mapping so the example runs during checks
SummarizedExperiment::colData(se) <- S4Vectors::DataFrame(
    sample_type = rep(c('Normal', 'Tumor'), length.out = ncol(se)),
    row.names = colnames(se)
)
calculate_lm_interaction(se, sample_type_col = 'sample_type')
#> data frame with 0 columns and 0 rows