API for gillislab/MetaMarkers
Extract robust markers from multiple datasets

Global functions
assign_cells Man page Source code
assign_cells_ Source code
auroc_p_value Source code
average_expression Source code
colVars_sparse Source code
compute_aurocs Man page Source code
compute_marker_enrichment Man page Source code
compute_markers Man page Source code
compute_markers_ Source code
compute_markers_blockwise Source code
compute_tie_correction Source code
compute_umap Man page
convert_to_cpm Man page Source code
design_matrix Man page Source code
export_markers Man page Source code
export_markers_by_cell_type Man page Source code
export_markers_by_group Man page Source code
export_markers_for_cell_type Man page Source code
export_meta_markers Man page Source code
export_meta_markers_by_cell_type Man page Source code
find_common_genes Source code
get_cell_type Man page Source code
get_group Man page Source code
get_pareto_markers Man page Source code
gmean Source code
is_pareto_front Source code
make_meta_markers Man page Source code
marker_list_to_matrix Man page Source code
marker_table_to_matrix Man page Source code
my_col_sums Source code
my_fdr Source code
plot_assignments Man page
plot_marker_expression Man page Source code
plot_marker_scores Man page
plot_pareto_markers Man page Source code
plot_pareto_summary Man page Source code
rank_sparse Source code
rank_zero Source code
read_markers Man page Source code
read_meta_markers Man page Source code
remove_duplicated_genes Man page Source code
score_cells Man page Source code
summarize_auroc Man page Source code
summarize_fold_change Man page Source code
summarize_precision_recall Man page Source code
tidy_stat Source code
write_cell_type_header Source code
write_header Source code
write_meta_header Source code
gillislab/MetaMarkers documentation built on April 24, 2021, 9:25 p.m.