Package index • multideconv

Main

Public user-facing functions

compute.deconvolution(): Compute deconvolution
compute.deconvolution.analysis(): Compute cell type processing
aggregate_cell_groups(): Aggregate cell types into groups
replicate_deconvolution_subgroups(): Replicate deconvolution subgroups in a new dataset
compute.subgroup.pathways(): Relate Deconvolution Subgroups to Pathway Activities
prepare_multideconv_folds(): Prepare folds for multideconv cross-validation with processed training and test data

Public benchmarking workflow

Public single-cell utilities

create_metacells(): Create meta-cells from a single cell object using the KNN algorithm. This function is adapted from the R package hdWGCNA (Morabito et al., 2023)
create_sc_pseudobulk(): Create pseudo bulk from single cell object
create_sc_signatures(): Create cell type signatures from scRNAseq

Exported helper functions for the cell type nomenclature

get_cell_type_nomenclature(): Canonical cell type nomenclature used by multideconv
standardize_celltype_colnames(): Standardize Cell Type Column Names

Internal use (not exported functions)

compute.deconvolution.preprocessing(): Compute deconvolution preprocessing
compute_methods_variable_signature(): Compute deconvolution methods with variable signatures
compute_sc_deconvolution_methods(): Compute second-generation deconvolution methods
computeCBSX(): Computes CIBERSORTx (CBSX) using one signature
computeCBSX_parallel(): Compute CIBERSORTx (CBSX) in parallel across multiple signatures
computeDWLS(): Computes DWLS
computeDWLS_parallel(): Compute DWLS in parallel across multiple signatures
computeDeconRNASeq(): Computes DeconRNASeq
computeEpiDISH(): Computes EpiDISH
computeMOMF(): Computes MOMF
computeMOMF_parallel(): Compute MOMF in parallel across multiple signatures
computeQuantiseq(): Computes QuanTIseq
compute_subgroups(): Compute deconvolution subgroups
compute.cell.types(): Cell types split from deconvolution
corr_subgroups(): Perform pairwise correlation across all features
remove_low_variance(): Remove low variance deconvolution features
process_group(): Build metacells for one cell type and sample group
stratified_sample_cells(): Subsample cells per cell type
unregister_dopar(): Reset the foreach backend to sequential
ensure_results_dir(): Create the Results output directory

Example data