compute_posterior | Compute posterior according to Gamma-Poisson model |
compute_posterior.default | Compute posterior according to Gamma-Poisson model for... |
compute_posterior.eSVD | Compute posterior according to Gamma-Poisson model for eSVD... |
compute_pvalue | Compute p-values |
compute_test_statistic | Compute test statistics |
compute_test_statistic.default | Compute test statistics for matrices |
compute_test_statistic.eSVD | Compute test statistics for eSVD object |
data_loader | Internal data loader function |
dot-compute_df | Compute the degree of freedom |
dot-reparameterize | Function to reparameterize two matrices |
estimate_nuisance | Estimate nuisance values |
estimate_nuisance.default | Estimate nuisance values for matrix or sparse matrices. |
estimate_nuisance.eSVD | Estimate nuisance values for eSVD objects (i.e.,... |
esvd_family | Internal Constructor for distribution family |
fisher_test | Fisher's exact test |
format_covariates | Format covariates |
gandal_df | Gandal et al. results |
generate_data | Generate data |
generate_null | Generate null data |
housekeeping_df | Hounkpe et al. housekeeping genes |
initialize_esvd | Initialize eSVD |
multtest | Perform multiple-testing adjustment using Efron's empirical... |
opt_esvd | Optimize eSVD |
opt_esvd.default | Optimize eSVD for matrices or sparse matrices. |
opt_esvd.eSVD | Optimize eSVD for eSVD objects |
opt_x | Optimize X given C, Y and Z |
opt_yz | Optimize Y and Z given X and C |
print.esvd_data_loader | Internal data loader function |
reparameterization_esvd_covariates | Reparameterize eSVD object |
sfari_df | SFARI genes |
velmeshev_gene_df | Velmeshev et al. DEGs |
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