Meta Clustering with Similarity Network Fusion

Documentation for package ‘metasnf’ version 1.1.2

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-- A --

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_columns	Add columns to a dataframe
add_settings_matrix_rows	Add settings matrix rows
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_dl	Given a data_list object, sort data elements by subjectkey
assemble_data	Collapse a dataframe and/or a data_list into a single dataframe
assoc_pval_heatmap	Heatmap of pairwise associations between features
auto_plot	Automatically plot features across clusters

-- B --

bar_plot	Bar plot separating a feature by cluster
batch_nmi	Calculate feature NMIs for a data_list and a derived solutions_matrix
batch_row_closure	Generate closure function to run batch_snf in an apply-friendly format
batch_snf	Run variations of SNF.
batch_snf_subsamples	Run SNF clustering pipeline on a list of subsampled data lists.

-- C --

calculate_coclustering	Calculate coclustering data.
calculate_db_indices	Calculate Davies-Bouldin indices
calculate_dunn_indices	Calculate Dunn indices
calculate_silhouettes	Calculate silhouette scores
calc_aris	Meta-cluster calculations
calc_assoc_pval	Calculate p-values based on feature vectors and their types
calc_assoc_pval_matrix	Calculate p-values for all pairwise associations of features in a data_list
cancer_diagnosis_df	Mock diagnosis data
cell_significance_fn	Place significance stars on ComplexHeatmap cells.
char_to_fac	Convert character-type columns of a dataframe to factor-type
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
chi_squared_pval	Chi-squared test p-value (generic)
coclustering_coverage_check	Coclustering coverage check
cocluster_density	Density plot coclustering stability across subsampled data.
cocluster_heatmap	Heatmap of observation co-clustering across resampled data.
collapse_dl	Collapse a data_list into a single dataframe
colour_scale	Return a colour ramp for a given vector
convert_uids	Convert unique identifiers of data_list to 'subjectkey'
cort_sa	Mock ABCD cortical surface area data
cort_t	Mock ABCD cortical thickness data

-- D --

depress	Mock ABCD depression data
diagnosis_df	Mock diagnosis data
discretisation	Internal function for 'estimate_nclust_given_graph'
discretisation_evec_data	Internal function for 'estimate_nclust_given_graph'
dl_has_duplicates	Check if data list contains any duplicate features
dl_uid_first_col	Make the subjectkey UID columns of a data_list first
dl_variable_summary	Variable-level summary of a data_list
domains	Domains
domain_merge	SNF scheme: Domain merge
drop_inputs	Execute inclusion

-- E --

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	Distance metric: Euclidean distance
expression_df	Modification of SNFtool mock dataframe "Data1"
extend_solutions	Extend an solutions matrix to include outcome evaluations

-- F --

fav_colour	Mock ABCD "colour" data
fisher_exact_pval	Fisher exact test p-value

-- G --

gender_df	Mock gender data
generate_annotations_list	Generate annotations list
generate_clust_algs_list	Generate a list of custom clustering algorithms
generate_data_list	Generate a data_list
generate_distance_metrics_list	Generate a list of distance metrics
generate_settings_matrix	Build a settings matrix
generate_weights_matrix	Generate a matrix to store feature weights
get_clusters	Extract cluster membership vector from one solutions matrix row
get_cluster_df	Extract cluster membership information from one solutions matrix row
get_cluster_solutions	Extract cluster membership information from a solutions_matrix
get_complete_uids	Pull complete-data UIDs from a list of dataframes
get_dist_matrix	Calculate distance matrices
get_dl_subjects	Extract subjects 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_mean_pval	Get mean p-value
get_min_pval	Get minimum p-value
get_pvals	Get p-values from an extended solutions matrix
get_representative_solutions	Extract representative solutions from a matrix of ARIs
gower_distance	Distance metric: Gower distance

-- H --

hamming_distance

Distance metric: Hamming distance

-- I --

income	Mock ABCD income data
individual	SNF Scheme: Individual

-- J --

jitter_plot

Jitter plot separating a feature by cluster

-- L --

label_prop	Label propagation
label_splits	Convert a vector of partition indices into meta cluster labels
linear_adjust	Linearly correct data_list by features with unwanted signal
linear_model_pval	Linear model p-value (generic)
list_remove	Remove items from a data_list
lp_solutions_matrix	Label propagate cluster solutions to unclustered subjects

-- M --

mc_manhattan_plot	Manhattan plot of feature-meta cluster associaiton p-values
merge_data_lists	Horizontally merge compatible data lists
merge_df_list	Merge list of dataframes
methylation_df	Modification of SNFtool mock dataframe "Data2"

-- N --

no_subs	Select all columns of a dataframe not starting with the 'subject_' prefix.
numcol_to_numeric	Convert dataframe columns to numeric type

-- O --

ord_reg_pval

Ordinal regression p-value

-- P --

parallel_batch_snf	Parallel processing form of batch_snf
prefix_dl_sk	Add "subject_" prefix to all UID values in subjectkey column
pubertal	Mock ABCD pubertal status data
pval_heatmap	Heatmap of p-values

-- R --

random_removal	Generate random removal sequence
reduce_dl_to_common	Reduce data_list to common subjects
remove_dl_na	Remove NAs from a data_list object
rename_dl	Rename features in a data_list
reorder_dl_subs	Reorder the subjects in a data_list
resample	Helper resample function found in ?sample

-- S --

save_heatmap	Save a heatmap object to a file
scale_diagonals	Adjust the diagonals of a matrix
settings_matrix_heatmap	Heatmap for visualizing a settings matrix
sew_euclidean_distance	Squared (excluding weights) Euclidean distance
shiny_annotator	Launch shiny app to identify meta cluster boundaries
similarity_matrix_heatmap	Plot heatmap of similarity matrix
similarity_matrix_path	Generate a complete path and filename to store an similarity matrix
siw_euclidean_distance	Squared (including weights) Euclidean distance
snf_step	Convert a data list to a similarity matrix through a variety of SNF schemes
sn_euclidean_distance	Distance metric: Standard normalization then Euclidean
spectral_eigen	Clustering algorithm: Spectral clustering with eigen-gap heuristic
spectral_eigen_classic	Clustering algorithm: Spectral clustering with eigen-gap heuristic
spectral_eight	Clustering algorithm: Spectral clustering for a eight cluster solution
spectral_five	Clustering algorithm: Spectral clustering for a five cluster solution
spectral_four	Clustering algorithm: Spectral clustering for a four cluster solution
spectral_nine	Clustering algorithm: Spectral clustering for a nine cluster solution
spectral_rot	Clustering algorithm: Spectral clustering with rotation cost heuristic
spectral_rot_classic	Clustering algorithm: Spectral clustering with rotation cost heuristic
spectral_seven	Clustering algorithm: Spectral clustering for a seven cluster solution
spectral_six	Clustering algorithm: Spectral clustering for a six cluster solution
spectral_ten	Clustering algorithm: Spectral clustering for a ten cluster solution
spectral_three	Clustering algorithm: Spectral clustering for a three cluster solution
spectral_two	Clustering algorithm: Spectral clustering for a two cluster solution
split_parser	Helper function to determine which row and columns to split on
subc_v	Mock ABCD subcortical volumes data
subs	Select all columns of a dataframe starting with a given string prefix.
subsample_data_list	Create subsamples of a data_list
subsample_pairwise_aris	Calculate pairwise adjusted Rand indices across subsamples of data
summarize_clust_algs_list	Summarize a clust_algs_list object
summarize_dl	Summarize a data list
summarize_dml	Summarize metrics contained in a distance_metrics_list
summarize_pvals	Summarize p-value columns of an extended solutions matrix

-- T --

train_test_assign	Training and testing split
two_step_merge	Two step SNF

-- V --

var_manhattan_plot

Manhattan plot of feature-feature associaiton p-values