| add_import | add_import |
| annotate_clusters | annotate_clusters functionally annotates the identified clusters |
| bootstrap_parallel | BootStrap runs for both scGPS training and prediction with parallel option |
| bootstrap_prediction | BootStrap runs for both scGPS training and prediction |
| calcDist | Compute Euclidean distance matrix by rows |
| calcDistArma | Compute Euclidean distance matrix by rows |
| clustering | HC clustering for a number of resolutions |
| clustering_bagging | HC clustering for a number of resolutions |
| CORE_bagging | Main clustering SCORE (CORE V2.0) Stable Clustering at Optimal REsolution with bagging and bootstrapping |
| CORE_clustering | Main clustering CORE V2.0 updated |
| CORE_subcluster | sub_clustering (optional) after running CORE 'test' |
| day_2_cardio_cell_sample | One of the two example single-cell count matrices to be used for training 'scGPS' model |
| day_5_cardio_cell_sample | One of the two example single-cell count matrices to be used for 'scGPS' prediction |
| distvec | Compute Distance between two vectors |
| find_markers | find marker genes |
| find_optimal_stability | Find the optimal cluster |
| find_stability | Calculate stability index |
| mean_cpp | Calculate mean |
| new_scGPS_object | new_scGPS_object |
| new_summarized_scGPS_object | new_summarized_scGPS_object |
| PCA | PCA |
| plot_CORE | Plot dendrogram tree for CORE result |
| plot_optimal_CORE | plot one single tree with the optimal clustering result |
| plot_reduced | plot reduced data |
| predicting | Main prediction function applying the optimal ElasticNet and LDA models |
| PrinComp_cpp | Principal component analysis |
| rand_index | Calculate rand index |
| rcpp_Eucl_distance_NotPar | Function to calculate Eucledean distance matrix without parallelisation |
| rcpp_parallel_distance | distance matrix using C++ |
| reformat_LASSO | summarise bootstrap runs for Lasso model, from 'n' bootstraps |
| subset_cpp | Subset a matrix |
| sub_clustering | sub_clustering for selected cells |
| summary_accuracy | get percent accuracy for Lasso model, from 'n' bootstraps |
| summary_deviance | get percent deviance explained for Lasso model, from 'n' bootstraps |
| summary_prediction_lasso | get percent deviance explained for Lasso model, from 'n' bootstraps |
| summary_prediction_lda | get percent deviance explained for LDA model, from 'n' bootstraps |
| top_var | select top variable genes |
| tp_cpp | Transpose a matrix |
| training | Main model training function for finding the best model that characterises a subpopulation |
| training_gene_sample | Input gene list for training 'scGPS', e.g. differentially expressed genes |
| tSNE | tSNE |
| var_cpp | Calculate variance |