Package index • clusnalyst

The app

run_app(): Run the Clusnalyst app

Reading data

read_markers(): Read a data file into a Clusnalyst dataset
detect_format(): Guess the format of a data file
guess_type(): Guess the data type of a table
read_vcf(): Read a VCF file as SNP dosages
read_hapmap(): Read a HapMap genotype file
read_fasta(): Read a FASTA file
align_sequences(): Align sequences with the msa package
read_metadata(): Read a sample metadata table
attach_metadata(): Attach metadata to a dataset
genotypes_to_dosage(): Convert letter genotypes to allele dosages
data_types(): Data types Clusnalyst works with
sample_names(): Sample names of a Clusnalyst dataset
demo_info() clusnalyst_demo(): Demo datasets

Quality check

qc_summary(): Quality summary of a dataset
filter_data(): Filter markers, traits or sequences

Distances and trees

distance_choices(): Distance measures available for a data type
default_distance(): Default distance for a dataset
compute_distance(): Compute a distance matrix
tree_choices(): Tree-building methods
build_tree(): Build a tree from a distance matrix
cophenetic_cor(): Cophenetic correlation of a tree
cophenetic_table(): Compare tree methods by cophenetic correlation

Checking the tree

bootstrap_tree(): Bootstrap support for a tree
consensus_tree(): Majority-rule consensus of bootstrap trees
optimal_k(): Choose the number of clusters
silhouette_meaning(): How to read an average silhouette width
mantel_test(): Mantel test between two distance matrices
read_second_matrix(): Read a second matrix for a Mantel test
metadata_distance(): Distances from numeric metadata columns

Groups and ordination

ordinate(): Principal coordinates or principal components
partition(): Split samples into groups
has_numeric(): Can PCA or k-means be used on this dataset?

Plots

plot_heatmap(): Heatmap of a distance matrix
plot_k(): Plot the cluster-number diagnostics
plot_mantel(): Plot two distance matrices against each other
plot_ordination(): Plot an ordination
plot_qc(): Plot quality-check summaries
plot_scree(): Scree plot of an ordination
plot_support(): Plot bootstrap support values
plot_tree(): Plot a tree
cl_palette(): Colours for groups
theme_clusnalyst(): ggplot2 theme used by Clusnalyst

Whole analyses, reports and sessions

default_settings(): Default analysis settings
run_analysis(): Run a whole analysis from settings
build_script(): Write an R script that repeats an analysis
build_report(): Write a self-contained HTML report
save_session() load_session(): Save and restore an analysis session

Package

clusnalyst clusnalyst-package: clusnalyst: Point-and-Click Cluster Analysis of Molecular and Trait Data