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Welcome to the CauMedi vignette! This document provides an overview of the CauMedi package. CauMedi is a causal mediation framework for cell type-specific single-cell data based on joint mediator multilevel models. The framework jointly models overdispersed counts and zero inflation for the mediators.
Run prepare_CauMedi_data first to prepare inputs before running main function.
library(CauMedi)
set.seed(42)
n_subj <- 100
n_gene <- 50
gene_ids <- paste0("gene", seq_len(n_gene))
M_mat <- matrix(rgamma(n_subj * n_gene, shape = 2, rate = 1),
nrow = n_subj, ncol = n_gene,
dimnames = list(paste0("subj", seq_len(n_subj)), gene_ids))
F_mat <- matrix(runif(n_subj * n_gene, min = 0, max = 1),
nrow = n_subj, ncol = n_gene,
dimnames = list(paste0("subj", seq_len(n_subj)), gene_ids))
Y <- rnorm(n_subj)
X <- rbinom(n_subj, 1, 0.5)
feature_meta <- data.frame(
feature_id = gene_ids,
cell_type = "Vasculature_cells",
gene = gene_ids,
stringsAsFactors = FALSE
)
pd <- prep_CauMedi_data(M_mat = M_mat, F_mat = F_mat, feature_meta = feature_meta, Y = Y, X = X)Use outputs from prep_CauMedi_data function as inputs for main function CauMedi.
res <- CauMedi(data = pd$data, feature_meta = pd$feature_meta)
print(res)
#> $coef_outcome
#> (Intercept) X M_gene48 M_gene23 F_gene32 F_gene36
#> 0.01066148 0.17497867 0.04849605 -0.09506033 -0.09519435 -0.12306433
#> F_gene9 F_gene19 F_gene45 F_gene49
#> 0.01960922 0.10651115 -0.06703089 0.06287628
#>
#> $se_outcome
#> (Intercept) X M_gene48 M_gene23 F_gene32 F_gene36
#> 0.1659187 0.2581165 0.1139251 0.1119261 0.1115699 0.1128999
#> F_gene9 F_gene19 F_gene45 F_gene49
#> 0.1126850 0.1096564 0.1110100 0.1098068
#>
#> $gamma_coef_vec
#> M_gene48 M_gene23
#> 0.4532473 -0.3922426
#>
#> $gamma_se_vec
#> NULL
#>
#> $alpha_coef_vec
#> F_gene32 F_gene36 F_gene9 F_gene19 F_gene45 F_gene49
#> 0.5678107 -0.5490598 -0.4615541 -0.4605079 -0.4458847 0.4250634
#>
#> $alpha_se_vec
#> NULL
#>
#> $signif_M
#> named integer(0)
#>
#> $signif_F
#> named integer(0)
#>
#> $M_summary
#> cell_type mediator gene gamma p_gamma beta_M p_beta_M
#> 1 Vasculature_cells M_gene48 gene48 0.4532473 0.02266345 0.04849605 0.6713546
#> 2 Vasculature_cells M_gene23 gene23 -0.3922426 0.04934008 -0.09506033 0.3979606
#> joint_pval adj_pval
#> 1 0.6713546 0.6713546
#> 2 0.3979606 0.6713546
#>
#> $F_summary
#> cell_type mediator gene alpha p_alpha beta_F
#> 1 Vasculature_cells F_gene32 gene32 0.5678107 0.004007658 -0.09519435
#> 2 Vasculature_cells F_gene36 gene36 -0.5490598 0.005459492 -0.12306433
#> 3 Vasculature_cells F_gene9 gene9 -0.4615541 0.020233166 0.01960922
#> 4 Vasculature_cells F_gene19 gene19 -0.4605079 0.020526354 0.10651115
#> 5 Vasculature_cells F_gene45 gene45 -0.4458847 0.025022176 -0.06703089
#> 6 Vasculature_cells F_gene49 gene49 0.4250634 0.032854105 0.06287628
#> p_beta_F joint_pval adj_pval
#> 1 0.3957991 0.3957991 0.6820051
#> 2 0.2786097 0.2786097 0.6820051
#> 3 0.8622421 0.8622421 0.8622421
#> 4 0.3339938 0.3339938 0.6820051
#> 5 0.5474771 0.5474771 0.6820051
#> 6 0.5683376 0.5683376 0.6820051These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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