Package index • metasnf

All functions

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() deprecated: 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

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

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

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.

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

calculate_coclustering(): Calculate coclustering data.

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

spectral_eigen() spectral_rot() spectral_eigen_classic() spectral_rot_classic() spectral_two() spectral_three() spectral_four() spectral_five() spectral_six() spectral_seven() spectral_eight() spectral_nine() spectral_ten(): 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() deprecated: 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

euclidean_distance() gower_distance() sn_euclidean_distance() sew_euclidean_distance() hamming_distance(): Built-in distance functions

dist_fns_list(): Build a distance metrics list

dl_variable_summary() deprecated: Variable-level summary of a data list

dlapply(): Lapply-like function for data list objects

dplyr_row_slice.ext_solutions_df(): Function to extend dplyr to extended solutions data frame objects

dplyr_row_slice.solutions_df(): Function to extend dplyr to solutions data frame objects

esm_manhattan_plot(): Manhattan plot of feature-cluster association p-values

estimate_nclust_given_graph(): Estimate number of clusters for a similarity matrix

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() deprecated: Generate a clustering algorithms list

generate_distance_metrics_list() deprecated: Generate a list of distance metrics

generate_settings_matrix() deprecated: Build a settings data frame

get_cluster_df() deprecated: Extract cluster membership information from one solutions data frame row

get_cluster_solutions() deprecated: Extract cluster membership information from a sol_df

get_clusters() deprecated: Extract cluster membership vector from one solutions data frame row

get_complete_uids(): Pull complete-data UIDs from a list of data frames

get_dl_uids() deprecated: 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

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(<data_list>): Merge observations between two compatible data lists

merge(<snf_config>): Merge method for SNF config objects

merge_df_list(): Merge list of data frames into a single data frame

meta_cluster_heatmap(): Heatmap of pairwise adjusted rand indices between solutions

methylation_df: Modification of SNFtool mock data frame "Data2"

n_features(): Extract number of features stored in an object

n_observations(): Extract number of observations stored in an object

new_solutions_df(): Constructor for solutions_df class 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

calculate_silhouettes() calculate_dunn_indices() calculate_db_indices(): 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

shiny_annotator(): Launch a shiny app to identify meta cluster boundaries

sim_mats_list(): Create or extract a sim_mats_list class object

similarity_matrix_heatmap(): Plot heatmap of similarity matrix

siw_euclidean_distance(): Squared (including weights) Euclidean distance

snf_config(): Define configuration for generating a set of SNF-based cluster solutions

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() deprecated: 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