Package index • CellTFusion

Main

Full pipeline in one call

TF activity, TF co-activity modules and pathway activity

compute.TFs.activity(): Compute Transcription Factor (TF) activity
compute.WTCNA(): Compute Weighted TF-coactivity Network Analysis (WTCNA)
compute.pathway.activity(): Computes TF-modules pathway activities scores
identify_hub_TFs(): Identify hub TFs
compute.modules.enrichment(): Compute TF module enrichment using directed target genes
compute.modules.relationship(): Compute modules relationship

Cell group construction, NMF latent factors and cell niches

construct_cell_groups(): Construct cell groups based on TF networks and deconvolution
identify(<cell.groups>): Identify cell groups
cell.groups.computation(): Compute cell group scores from deconvolution and TF module network
compute_composite_score(): Compute composite score for cell groups
compute.composition.matrix(): Compute a cell-type composition matrix from deconvolution subgroups
extract_cells(): Extract cells from cell type groups
compute.latent_factors(): Compute latent factors from cell group scores using NMF
compute_cells_niches(): Identify cell-type niches from NMF latent factors

Hallmark GSEA, TCGA meta-programs and TME subtypes

compute_factor_gsea(): Run multivariate feature-based GSEA using limma and Hallmark gene sets
build_nes_matrix(): Build a Hallmarks x factors NES matrix from GSEA results
derive_meta_programs(): Derive TME meta-programs by clustering Hallmarks across NMF factors
map_factors_to_metaprograms(): Map study factors to TCGA meta-programs
map_factors_to_TME(): Annotate NMF factors with Bagaev et al. (2021) MFP subtypes
annotate_metaprograms_TME(): Annotate meta-programs with Bagaev TME subtypes

Associations with clinical variables and survival

scores.stat.analysis(): Perform statistical analysis on scores using a specified test
scores.wilcox.test(): Wilcoxon rank-sum test for binary traits
scores.ttest(): Student's t-test for cell group comparisons
scores.kruskal.test(): Kruskal-Wallis test for multi-group comparisons
scores.anova.test(): One-way ANOVA test for multi-group comparisons
scores.fisher.test(): Fisher's exact test for score-trait association
compute.metadata.association(): Compute associations between TF module scores and clinical metadata
compute.survival.analysis(): Kaplan-Meier survival analysis on clinical groups or CellTFusion features

Leakage-aware cross-validation with pipeML and projection of independent data

prepare_celltfusion_folds(): Prepare CellTFusion cross-validation folds for pipeML
project_test_factors(): Project test-set samples onto training NMF factors
compute.test.set(): Compute composite scores on test set based on previous cell groups
project_factors(): Project cell group scores onto trained NMF latent factors

Example data