lr_linear_model_discrete {PopComm} | R Documentation |
Compare Ligand-Receptor Interaction Scores with Group Variable using Linear Regression
Description
Perform linear regression analysis to compare ligand-receptor (LR) interaction scores across groups, handling both continuous and binary group variables (ident1 vs ident2 or all others).
Usage
lr_linear_model_discrete(
lr_scores,
metadata,
group_variable,
ident1,
ident2 = NULL,
covariates = NULL,
fdr_threshold = 0.05
)
Arguments
lr_scores |
Data frame containing LR interaction scores per sample (data frame). |
metadata |
Data frame containing sample metadata (data frame). |
group_variable |
Column name in |
ident1 |
If categorical, group to compare (coded as 1) (character). |
ident2 |
Reference group or list of groups (coded as 0). If None, uses all others (character). |
covariates |
Optional list of covariate column names (character vector). |
fdr_threshold |
Significance cutoff for adjusted p-values (numeric, default: 0.05). |
Value
Data frame with ligand, receptor, sender, receiver, coef (coefficient, logFC), p-values, and adjusted p-values.
Examples
# Long-running example (may take >10s)
data(lr_scores_eg)
data(metadata_eg)
res <- lr_linear_model_discrete(
lr_scores_eg, metadata_eg,
group_variable = "IFN_type",
ident1 = "high",
covariates = c("Age_group", "Sex")
)
head(res)