Function reference • diceR

Functions

consensus_cluster(): Consensus clustering

consensus_combine(): Combine algorithms

consensus_evaluate(): Evaluate, trim, and reweigh algorithms

consensus_matrix(): Consensus matrix

graph_cdf() graph_delta_area() graph_heatmap() graph_tracking() graph_all(): Graphical Displays

ev_nmi() ev_confmat(): External validity indices

impute_knn(): K-Nearest Neighbours imputation

impute_missing(): Impute missing values

pcn_simulate() pcn_select(): Simulate and select null distributions on empirical gene-gene correlations

dice(): Diverse Clustering Ensemble

CSPA(): Cluster-based Similarity Partitioning Algorithm (CSPA)

k_modes(): K-modes

majority_voting(): Majority voting

LCE(): Linkage Clustering Ensemble

LCA(): Latent Class Analysis

PAC(): Proportion of Ambiguous Clustering

cts() srs() asrs(): Similarity Matrices

compactness(): Compactness Measure

prepare_data(): Prepare data for consensus clustering

relabel_class(): Relabel classes to a standard

min_fnorm(): Minimize Frobenius norm for between two matrices

sigclust(): Significant Testing of Clustering Results

Data

hgsc: Gene expression data for High Grade Serous Carcinoma from TCGA

Package Documentation

diceR diceR-package: diceR: Diverse Cluster Ensemble in R