Package index • CellTFusion

Main

Compute cell type deconvolution

CellTFusion(): Compute one-step CellTFusion
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
compute_factor_gsea(): Run multivariate feature-based GSEA using limma and Hallmark gene sets
identify_hub_TFs(): Identify hub TFs
construct_cell_groups(): Construct cell groups based on TF networks and deconvolution
compute(<test.set>): Compute composite scores on test set based on previous cell groups

Visualization

compute(<metadata.association>): Compute associations between TF module scores and clinical metadata
compute(<modules.relationship>): Compute modules relationship
compute(<modules.enrichment>): Compute TF module enrichment using directed target genes

Cell groups analysis

scores.fisher.test(): Fisher's exact test for score-trait association
scores.anova.test(): One-way ANOVA test for multi-group comparisons
scores.wilcox.test(): Wilcoxon rank-sum test for binary traits
scores.kruskal.test(): Kruskal-Wallis test for multi-group comparisons
scores.ttest(): Student's t-test for cell group comparisons
scores.stat.analysis(): Perform statistical analysis on scores using a specified test
compute(<latent_factors>): Compute latent factors from cell group scores using NMF
identify(<cell.groups>): Identify cell groups

Meta-program derivation and TME mapping

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
build_nes_matrix(): Build a Hallmarks x factors NES matrix from GSEA results
project_factors(): Project cell group scores onto trained NMF latent factors
project_test_factors(): Project test-set samples onto training NMF factors

Internal use (not exported functions)

cell.groups.computation(): Compute cell group scores from deconvolution and TF module network
classify.deconvolution(): Classify samples by high or low deconvolution values in given cell groups
compute(<TF.network.classification>): Compute TF Network Classification
compute(<composition.matrix>): Compute a cell-type composition matrix from deconvolution subgroups
compute_composite_score(): Compute composite score for cell groups
create_tfs_modules(): Create TFs modules
extract_cells(): Extract cells from cell type groups
extract_colors(): Extract colors
extract_wilcox_significant(): Extract significant features using Wilcoxon test

Example data