Function reference • musicatk

Importing and processing Functions to import, extract, and process variants
`extract_variants()`	Extract variants from mutliple objects
`extract_variants_from_maf()`	Extract variants from a maf object
`extract_variants_from_maf_file()`	Extracts variants from a maf file
`extract_variants_from_matrix()`	Extract variants from matrix or data.frame like objects
`extract_variants_from_vcf()`	Extracts variants from a VariantAnnotation VCF object
`extract_variants_from_vcf_file()`	Extracts variants from a vcf file
musica objects Functions to create and subset musica objects
`select_genome()`	Helper function to load common human or mouse genomes
`create_musica()`	Creates a musica object from a variant table
`subset_musica_by_annotation()`	Creates a new musica object subsetted to only one value of a sample annotation
`subset_musica_by_counts()`	Creates a new musica subsetted to only samples with enough variants
`subset_variant_by_type()`	Subsets a variant table based on Variant Type
`subset_variants_by_samples()`	Return sample from musica_variant object
`variants()` `variants<-`()	Retrieve variants from a musica or musica_result object
Creating mutation count tables Functions to build and combine mutation count tables
`build_standard_table()`	Builds count tables using various mutation type schemas
`build_custom_table()`	Builds a custom table from specified user variants
`add_flank_to_variants()`	Uses a genome object to find context and add it to the variant table
`annotate_replication_strand()`	Add replication strand annotation to SBS variants based on bedgraph file
`annotate_transcript_strand()`	Add transcript strand annotation to SBS variants (defined in genes only)
`annotate_variant_length()`	Adds an annotation to the input musica's variant table with length of each variant
`annotate_variant_type()`	Annotate variants with variant type ("SBS", "INS", "DEl", "DBS")
`combine_count_tables()`	Combines tables into a single table that can be used for discovery/prediction
`extract_count_tables()`	Extract count tables list from a musica object
`tables()` `tables<-`()	Retrieve the list of count_tables from a musica or musica_result object
Sample annotations Functions to add and manipulate sample annotations
`samp_annot()` `samp_annot<-`()	Get or set sample annotations from a musica or musica_result object
`sample_names()`	Retrieve sample names from a musica or musica_result object
`drop_annotation()`	Drops a column from the variant table that the user no longer needs
Discovery and prediction Functions to identify signatures and exposures from mutation count tables
`discover_signatures()`	Discover mutational signatures
`exposures()` `exposures<-`()	Retrieve exposures from a musica_result object
`signatures()` `signatures<-`()	Retrieve signatures from a musica_result object
`name_signatures()`	Return sample from musica object
`auto_predict_grid()`	Automatic filtering of signatures for exposure prediction gridded across specific annotation
`combine_predict_grid()`	Combine prediction grid list into a result object. Exposure values are zero for samples in an annotation where that signature was not predicted
`generate_result_grid()`	Generate result_grid from musica based on annotation and range of k
Visualization Functions to identify signatures and exposures from mutation count tables
`plot_exposures()`	Display sample exposures with bar, box, or violin plots
`plot_signatures()`	Plots the mutational signatures
`plot_umap()`	Plot a UMAP from a musica result
`plot_cluster()`	Visualize clustering results
`plot_differential_analysis()`	Compare exposures of annotated samples
`plot_heatmap()`	Plot heatmaps using the exposures matrix
`plot_sample_counts()`	Plot distribution of sample counts
`plot_sample_reconstruction_error()`	Plot reconstruction error for a sample
`predict_exposure()`	Prediction of exposures in new samples using pre-existing signatures
Downstream analysis Functions to compare the signatures between two results objects
`create_umap()`	Create a UMAP from a musica result
`umap()` `umap<-`()	Retrieve umap list from a musica_result object
`cluster_exposure()`	Perform clustering analysis from a musica result object
`k_select()`	Plots for helping decide number of clusters
Signature comparisons Functions to compare the signatures between two results objects
`compare_cosmic_v2()`	Compare a result object to COSMIC V2 SBS Signatures (combination whole-exome and whole-genome)
`compare_cosmic_v3()`	Compare a result object to COSMIC V3 Signatures; Select exome or genome for SBS and only genome for DBS or Indel classes
`compare_results()`	Compare two result files to find similar signatures
`exposure_differential_analysis()`	Compare exposures of annotated samples
COSMIC signatures Result objects that contain COSMIC signatures
`cosmic_v2_sigs`	COSMIC v2 SBS96 Signatures Result Object
`cosmic_v3_dbs_sigs`	COSMIC v3 DBS Genome Signatures Result Object
`cosmic_v3_indel_sigs`	COSMIC v3 Indel Genome Signatures Result Object
`cosmic_v3_sbs_sigs`	COSMIC v3 SBS96 Genome Signatures Result Object
`cosmic_v3_sbs_sigs_exome`	COSMIC v3 SBS96 Exome Signatures Result Object
Miscellaneous functions
`cosmic_v2_subtype_map()`	Input a cancer subtype to return a list of related COSMIC signatures
`get_musica()`	Retrieve musica from a musica_result object
Data objects and classes
`musica_sbs96`	musica_sbs96
`musica_sbs96_tiny`	musica_sbs96_tiny
`dbs_musica`	dbs_musica
`indel_musica`	indel_musica
`musica`	musica
`musica_annot`	musica_annot
`res`	res
`res_annot`	res_annot
`rep_range`	Replication Timing Data as GRanges Object
`musica-class`	The primary object that contains variants, count_tables, and samples annotations
`count_table-class`	Object containing the count table matrices, their names and descriptions that we generated by provided and by user functions. These are used to discover and infer signatures and exposures.
`musica_result-class`	Object containing deconvolved/predicted signatures, sample weights, and the musica object the result was generated from
`musica_result_grid-class`	Object containing the result objects generated from the combination of annotations and a range of k values

Reference

Importing and processing

musica objects

Creating mutation count tables

Sample annotations

Discovery and prediction

Visualization

Downstream analysis

Signature comparisons

COSMIC signatures

Miscellaneous functions

Data objects and classes