Function reference • immunarch

Bulk and single-cell data
Loading and saving any data
`repLoad()`	Load immune repertoire files into the R workspace
`repSave()`	Save immune repertoires to the disk
Filtering data
`repFilter()`	Main function for data filtering
Single-cell More coming soon!
`select_barcodes()`	Select specific clonotypes using barcodes from single-cell metadata
`select_clusters()`	Split the immune repertoire data to clusters from single-cell barcodes
Preprocessing
`bunch_translate()`	Nucleotide to amino acid sequence translation
`coding()` `noncoding()` `inframes()` `outofframes()`	Filter out coding and non-coding clonotype sequences
`repSample()`	Downsampling and resampling of immune repertoires
`top()`	Get the N most abundant clonotypes
BCR data
Clustering
`seqDist()`	Function for computing distance for sequences
`seqCluster()`	Function for assigning clusters based on sequences similarity
BCR pipeline
`repGermline()`	Creates germlines for clonal lineages
`repAlignLineage()`	Aligns all sequences incliding germline within each clonal lineage within each cluster
`repClonalFamily()`	Builds a phylogenetic tree using the sequences of a clonal lineage
`vis(<clonal_family>)`	Visualise clonal family tree: wrapper for calling on the entire repClonalFamily output
`vis(<clonal_family_tree>)`	Visualise clonal family tree
`repSomaticHypermutation()`	Calculates number of mutations against the germline for each clonotype
Basic immune repertoire statistics
Exploratory data analysis
`repExplore()`	Main function for exploratory data analysis: compute the distribution of lengths, clones, etc.
`vis(<immunr_exp_vol>)`	Visualise results of the exploratory analysis
Clonality analysis
`repClonality()`	Clonality analysis of immune repertoires
`vis(<immunr_clonal_prop>)`	Visualise results of the clonality analysis
Clonotype annotation and dynamics
Clonotype annotation Annotate clonotypes in immune repertoires using external immune receptor databases (VDJDB, McPAS and PIRD).
`dbAnnotate()`	Annotate clonotypes in immune repertoires using clonotype databases such as VDJDB and MCPAS
`dbLoad()`	Load clonotype databases such as VDJDB and McPAS into the R workspace
Immune repertoire dynamics Track the differences in clonotype abundances over time.
`trackClonotypes()`	Track clonotypes across time and data points
`vis(<immunr_dynamics>)`	Visualise clonotype dynamics
Compare repertoires
Repertoire diversity analysis
`repDiversity()`	The main function for immune repertoire diversity estimation
`vis(<immunr_chao1>)`	Visualise diversity.
Gene usage V-gene and J-gene usage statistics, analysis and visualisations
`geneUsage()`	Main function for estimation of V-gene and J-gene statistics
`geneUsageAnalysis()`	Post-analysis of V-gene and J-gene statistics: PCA, clustering, etc.
`gene_stats()`	WIP
`vis(<immunr_gene_usage>)`	Histograms and boxplots (general case / gene usage)
Overlap
`repOverlap()`	Main function for public clonotype statistics calculations
`repOverlapAnalysis()`	Post-analysis of public clonotype statistics: PCA, clustering, etc.
`inc_overlap()`	Incremental counting of repertoire similarity
`vis(<immunr_inc_overlap>)`	Visualise incremental overlaps
`vis(<immunr_ov_matrix>)`	Repertoire overlap and gene usage visualisations
Public repertoire
`pubRep()`	Create a repertoire of public clonotypes
`pubRepApply()`	Apply transformations to public repertoires
`pubRepFilter()`	Filter out clonotypes from public repertoires
`pubRepStatistics()`	Statistics of number of public clonotypes for each possible combinations of repertoires
`public_matrix()`	Get a matrix with public clonotype frequencies
`vis(<immunr_public_repertoire>)`	Public repertoire visualisation
`vis(<immunr_public_statistics>)`	Visualise sharing of clonotypes among samples
`vis_public_clonotypes()`	Visualisation of public clonotypes
`vis_public_frequencies()`	Public repertoire visualisation
Advanced immune repertoire analysis
Kmers analysis
`getKmers()`	Calculate the k-mer statistics of immune repertoires
`split_to_kmers()` `kmer_profile()`	Analysis immune repertoire kmer statistics: sequence profiles, etc.
Post-analysis Advanced methods for post-analysis of gene usage, overlap and other statistics.
`immunr_hclust()` `immunr_kmeans()` `immunr_dbscan()`	Clustering of objects or distance matrices
`immunr_pca()` `immunr_mds()` `immunr_tsne()`	Dimensionality reduction
`vis(<immunr_hclust>)`	Visualisation of hierarchical clustering
`vis(<immunr_kmeans>)`	Visualisation of K-means and DBSCAN clustering
`vis(<immunr_mds>)`	PCA / MDS / tSNE visualisation (mainly overlap / gene usage)
Visualisations
General visualisation functions Functions for visualisations of different data types. For analysis-specific visualisation see related sections.
`vis()`	One function to visualise them all
`vis(<clonal_family>)`	Visualise clonal family tree: wrapper for calling on the entire repClonalFamily output
`vis(<clonal_family_tree>)`	Visualise clonal family tree
`vis(<immunr_chao1>)`	Visualise diversity.
`vis(<immunr_clonal_prop>)`	Visualise results of the clonality analysis
`vis(<immunr_dynamics>)`	Visualise clonotype dynamics
`vis(<immunr_exp_vol>)`	Visualise results of the exploratory analysis
`vis(<immunr_gene_usage>)`	Histograms and boxplots (general case / gene usage)
`vis(<immunr_hclust>)`	Visualisation of hierarchical clustering
`vis(<immunr_inc_overlap>)`	Visualise incremental overlaps
`vis(<immunr_kmeans>)`	Visualisation of K-means and DBSCAN clustering
`vis(<immunr_kmer_table>)`	Most frequent kmers visualisation.
`vis(<immunr_mds>)`	PCA / MDS / tSNE visualisation (mainly overlap / gene usage)
`vis(<immunr_ov_matrix>)`	Repertoire overlap and gene usage visualisations
`vis(<immunr_public_repertoire>)`	Public repertoire visualisation
`vis(<immunr_public_statistics>)`	Visualise sharing of clonotypes among samples
`vis(<step_failure_ignored>)`	Handler for .nofail argument of pipeline steps that prevents examples from crashing on computers where certain dependencies are not installed
`vis_bar()`	Bar plots
`vis_box()`	Flexible box-plots for visualisation of distributions
`vis_circos()`	Visualisation of matrices using circos plots
`vis_heatmap()`	Visualisation of matrices and data frames using ggplo2-based heatmaps
`vis_heatmap2()`	Visualisation of matrices using pheatmap-based heatmaps
`vis_hist()`	Visualisation of distributions using histograms
`vis_immunr_kmer_profile_main()`	Visualise kmer profiles
`vis_public_clonotypes()`	Visualisation of public clonotypes
`vis_public_frequencies()`	Public repertoire visualisation
`vis_textlogo()` `vis_seqlogo()`	Sequence logo plots for amino acid profiles.
`spectratype()`	Immune repertoire spectratyping
Publication-ready plots
`fixVis()`	Manipulate ggplot plots and create publication-ready plots
Utilities
Data
`aa_properties` `properties` `kidera` `KIDERA` `aa_prop` `AA_PROP` `atchley` `ATCHLEY`	Tables with amino acid properties
`AA_TABLE`	Amino acid / codon table
`bcrdata`	BCR dataset
`gene_segments` `genes` `segments` `GENE_SEGMENTS`	Gene segments table
`immdata`	Single chain immune repertoire dataset
`immunr_data_format` `immunarch_data_format`	Specification of the data format used by immunarch dataframes
`scdata`	Paired chain immune repertoire dataset
Public utility utilities
`apply_symm()` `apply_asymm()`	Apply function to each pair of data frames from a list.
`entropy()` `kl_div()` `js_div()` `cross_entropy()`	Information measures
Internal utility functions
`add_class()`	Add a new class attribute
`check_distribution()`	Check and normalise distributions
`.quant_column_choice()`	Get a column's name using the input alias
`group_from_metadata()`	Get a character vector of samples' groups from the input metadata file
`has_class()`	Check for the specific class
`matrixdiagcopy()`	Copy the upper matrix triangle to the lower one
`set_pb()` `add_pb()`	Set and update progress bars
`switch_type()` `process_col_argument()`	Return a column's name

Reference

Bulk and single-cell data

Loading and saving any data

Filtering data

Single-cell

Preprocessing

BCR data

Clustering

BCR pipeline

Basic immune repertoire statistics

Exploratory data analysis

Clonality analysis

Clonotype annotation and dynamics

Clonotype annotation

Immune repertoire dynamics

Compare repertoires

Repertoire diversity analysis

Gene usage

Overlap

Public repertoire

Advanced immune repertoire analysis

Kmers analysis

Post-analysis

Visualisations

General visualisation functions

Publication-ready plots

Utilities

Data

Public utility utilities

Internal utility functions