A B C D E F G H I J L M N P Q R S T U V W
abcd_anxiety | Mock ABCD anxiety data |
abcd_colour | Mock ABCD "colour" data |
abcd_cort_sa | Mock ABCD cortical surface area data |
abcd_cort_t | Mock ABCD cortical thickness data |
abcd_depress | Mock ABCD depression data |
abcd_h_income | Mock ABCD income data |
abcd_income | Mock ABCD income data |
abcd_pubertal | Mock ABCD pubertal status data |
abcd_subc_v | Mock ABCD subcortical volumes data |
add_settings_df_rows | Add rows to a settings_df |
adjusted_rand_index_heatmap | Heatmap of pairwise adjusted rand indices between solutions |
age_df | Mock age data |
alluvial_cluster_plot | Alluvial plot of patients across cluster counts and important features |
anxiety | Mock ABCD anxiety data |
arrange | Arrange rows in an object |
as.data.frame.data_list | Coerce a 'data_list' class object into a 'data.frame' class object |
as.data.frame.ext_solutions_df | Coerce a 'ext_solutions_df' class object into a 'data.frame' class object |
as.data.frame.solutions_df | Coerce a 'solutions_df' class object into a 'data.frame' class object |
assemble_data | Collapse a data frame and/or a data list into a single data frame |
assoc_pval_heatmap | Heatmap of pairwise associations between features |
as_ari_matrix | Convert an object to an ARI matrix |
as_data_list | Convert an object to a data list |
as_settings_df | Convert an object to a settings data frame |
as_sim_mats_list | Convert an object to a similarity matrix list |
as_snf_config | Convert an object to a snf config |
as_weights_matrix | Convert an object to a weights matrix |
auto_plot | Automatically plot features across clusters |
bar_plot | Bar plot separating a feature by cluster |
batch_snf | Run variations of SNF. |
batch_snf_subsamples | Run SNF clustering pipeline on a list of subsampled data lists. |
calculate_coclustering | Calculate coclustering data. |
calculate_db_indices | Quality metrics |
calculate_dunn_indices | Quality metrics |
calculate_silhouettes | Quality metrics |
calc_aris | Construct an ARI matrix storing inter-solution similarities |
calc_assoc_pval_matrix | Calculate p-values for all pairwise associations of features in a data list |
calc_nmis | Calculate feature NMIs for a data list and a solutions data frame |
cancer_diagnosis_df | Mock diagnosis data |
cell_significance_fn | Place significance stars on ComplexHeatmap cells. |
check_dataless_annotations | Helper function to stop annotation building when no data was provided |
check_hm_dependencies | Check for ComplexHeatmap and circlize dependencies |
check_similarity_matrices | Check validity of similarity matrices |
clust_fns | Built-in clustering algorithms |
clust_fns_list | Build a clusteing algorithms list |
cocluster_density | Density plot coclustering stability across subsampled data. |
cocluster_heatmap | Heatmap of observation co-clustering across resampled data. |
collapse_dl | Convert a data list into a data frame |
colour_scale | Return a colour ramp for a given vector |
config_heatmap | Heatmap for visualizing an SNF config |
cort_sa | Mock ABCD cortical surface area data |
cort_t | Mock ABCD cortical thickness data |
data_list | Build a 'data_list' class object |
depress | Mock ABCD depression data |
diagnosis_df | Mock diagnosis data |
dist_fns | Built-in distance functions |
dist_fns_list | Build a distance metrics list |
dlapply | Lapply-like function for data list objects |
dl_variable_summary | Variable-level summary of a data list |
esm_manhattan_plot | Manhattan plot of feature-cluster association p-values |
estimate_nclust_given_graph | Estimate number of clusters for a similarity matrix |
euclidean_distance | Built-in distance functions |
expression_df | Modification of SNFtool mock data frame "Data1" |
extend_solutions | Extend a solutions data frame to include outcome evaluations |
fav_colour | Mock ABCD "colour" data |
features | Return character vector of features stored in an object |
gender_df | Mock gender data |
generate_clust_algs_list | Generate a clustering algorithms list |
generate_distance_metrics_list | Generate a list of distance metrics |
generate_settings_matrix | Build a settings data frame |
get_clusters | Extract cluster membership vector from one solutions data frame row |
get_cluster_df | Extract cluster membership information from one solutions data frame row |
get_cluster_solutions | Extract cluster membership information from a sol_df |
get_complete_uids | Pull complete-data UIDs from a list of data frames |
get_dl_uids | Extract UIDs from a data list |
get_heatmap_order | Return the row or column ordering present in a heatmap |
get_matrix_order | Return the hierarchical clustering order of a matrix |
get_pvals | Get p-values from an extended solutions data frame |
get_representative_solutions | Extract representative solutions from a matrix of ARIs |
gower_distance | Built-in distance functions |
hamming_distance | Built-in distance functions |
income | Mock ABCD income data |
is_data_list | Test if the object is a data list |
jitter_plot | Jitter plot separating a feature by cluster |
label_meta_clusters | Assign meta cluster labels to rows of a solutions data frame or extended solutions data frame |
label_propagate | Label propagate cluster solutions to unclustered observations |
linear_adjust | Linearly correct data list by features with unwanted signal |
mc_manhattan_plot | Manhattan plot of feature-meta cluster associaiton p-values |
merge.snf_config | Merge method for SNF config objects |
merge_df_list | Merge list of data frames into a single data frame |
merge_dls | Horizontally merge compatible data lists |
meta_cluster_heatmap | Heatmap of pairwise adjusted rand indices between solutions |
methylation_df | Modification of SNFtool mock data frame "Data2" |
new_solutions_df | Constructor for 'solutions_df' class object |
n_features | Extract number of features stored in an object |
n_observations | Extract number of observations stored in an object |
print.ari_matrix | Print method for class 'ari_matrix' |
print.clust_fns_list | Print method for class 'clust_fns_list' |
print.data_list | Print method for class 'data_list' |
print.dist_fns_list | Print method for class 'dist_fns_list' |
print.ext_solutions_df | Print method for class 'ext_solutions_df' |
print.settings_df | Print method for class 'settings_df' |
print.snf_config | Print method for class 'snf_config' |
print.solutions_df | Print method for class 'weights_matrix' |
print.t_ext_solutions_df | Print method for class 't_ext_solutions_df' |
print.t_solutions_df | Print method for class 't_solutions_df' |
print.weights_matrix | Print method for class 'weights_matrix' |
pubertal | Mock ABCD pubertal status data |
pval_heatmap | Heatmap of p-values |
quality_measures | Quality metrics |
random_removal | Generate random removal sequence |
rbind.ext_solutions_df | Row-binding of solutions data frame class objects. |
rbind.solutions_df | Row-binding of solutions data frame class objects. |
rename_dl | Rename features in a data list |
resample | Helper resample function found in ?sample |
save_heatmap | Save a heatmap object to a file |
settings_df | Build a settings data frame |
sew_euclidean_distance | Built-in distance functions |
shiny_annotator | Launch a shiny app to identify meta cluster boundaries |
similarity_matrix_heatmap | Plot heatmap of similarity matrix |
sim_mats_list | Create or extract a 'sim_mats_list' class object |
siw_euclidean_distance | Squared (including weights) Euclidean distance |
snf_config | Define configuration for generating a set of SNF-based cluster solutions |
sn_euclidean_distance | Built-in distance functions |
spectral_eigen | Built-in clustering algorithms |
spectral_eigen_classic | Built-in clustering algorithms |
spectral_eight | Built-in clustering algorithms |
spectral_five | Built-in clustering algorithms |
spectral_four | Built-in clustering algorithms |
spectral_nine | Built-in clustering algorithms |
spectral_rot | Built-in clustering algorithms |
spectral_rot_classic | Built-in clustering algorithms |
spectral_seven | Built-in clustering algorithms |
spectral_six | Built-in clustering algorithms |
spectral_ten | Built-in clustering algorithms |
spectral_three | Built-in clustering algorithms |
spectral_two | Built-in clustering algorithms |
split_parser | Helper function to determine which row and columns to split on |
subc_v | Mock ABCD subcortical volumes data |
subsample_dl | Create subsamples of a data list |
subsample_pairwise_aris | Calculate pairwise adjusted Rand indices across subsamples of data |
summarize_clust_fns_list | Summarize a clust_fns_list object |
summarize_dfl | Summarize metrics contained in a dist_fns_list |
summarize_dl | Summarize a data list |
summary.data_list | Summary method for class 'data_list' |
summary_features | Pull features used to calculate summary p-values from an object |
train_test_assign | Training and testing split |
uids | Pull UIDs from an object |
validate_solutions_df | Validator for 'solutions_df' class object |
var_manhattan_plot | Manhattan plot of feature-feature association p-values |
weights_matrix | Generate a matrix to store feature weights |