Magics {MedZIsc}R Documentation

Magics

Description

A main function for conducting causal mediation analysis with co-mediators derived from zero-inflated single-cell data.

Usage

Magics(data.name, n_genes, covariate.names)

Arguments

data.name

A data.frame or matrix with N x (2G + k), where N is the number of samples, G is the number of genes (each gene contributes two features: one for the zero component and one for the non-zero component), and K is the number of covariates.

n_genes

An interger value. The number of genes (G) represented in the data.

covariate.names

A character vector to specify the column name of covariates.

Value

A list containing the following elements: (1) estimated coefficients from the outcome and two mediation models (M and F models in methodology paper); (2) standard errors corresponding to (1); (3) logical vector indicating whether each gene's mediator component (M model) is statistically significant; (4) logical vector indicating whether each gene's zero-inflation component (F model) is statistically significant; (5) Adjusted p-values for M and F model (joint significance test).

References

Ahn S, Li Z. A Statistical Framework for Co-Mediators of Zero-Inflated Single-Cell RNA-Seq Data. ArXiv. 2025 July 8:arXiv:2507.06113v1. Available at: https://arxiv.org/pdf/2507.06113

Examples


data("simulated_data")
n_genes = ncol(simulated_data[, grep("^(M_)", colnames(simulated_data))])
Magics(data.name = simulated_data, n_genes = n_genes, covariate.names = c("Z1", "Z2", "Z3"))


[Package MedZIsc version 0.0.4 Index]