Function reference • pdtools

All functions

build_ppanggolin_file_fastas(): Build a ppanggolin file from fastas

calculate_novelty(): Calculate genome 'novelty' from a list of selection sets returned by pick_derep_sets

cluster_genomes(): Cluster genomes at 4 levels from a pangenome gene PA matrix Needs parallelDist, igraph, genomes as rows and genes as columns?

country_vector: A named vector of country names

download_PDD_metadata(): Download Pathogen Detection metadata for a given organism

download_SNP_trees(): Download SNP trees from a dataframe containing SNP_tree_urls and dests

download_gbk_assembly_summary(): Convenience function to download the assembly_summary.txt file from genbank

download_genomes(): Download a set of specified genome files

download_most_recent_complete(): Download the most recent complete metadata for a specified organism

download_reference_genomes(): Download reference genomes

example_pan_dist: A distance matrix describing the jaccard distance between genomes in the provided example pangenome

example_pangenome_matrix: A gene presence absence matrix for a synthetic pangenome

extract_collection_agency(): extract collecting agency from several metadata fields

extract_consensus_ag_species(): Extract a consensus ag host species from metadata This is pretty crude and should not be relied on for 100% accuracy

extract_country(): Extract a standardized country name from geo_loc_tag column

extract_earliest_year(): return a Year column containing the earliest year from the available 'date' fields.

extract_state(): Extract the state name from the geo_loc_name column, this only makes sence for USA isolates

get_PDG_version(): get the version of the PDD metadata

get_organism_table(): Load the organism summary table

get_pangenome_representatives(): Select a minimum set of genomes that best represent the gene content of the pangenome

get_pangenome_representatives_jaccard(): Get a subset of a pangenome that tries to represent the gene presence absence diversity Selects a random genome, then selects the most distant genome from the selected genome then

klebsiella_example_dat: NCBI Pathogen Detection metadata for 200 Klebsiella isolates

list_PDGs(): List available PDG accessions for an organism

list_organisms(): List organisms available in the Pathogens database

make_SNP_tree_dest(): Make SNP tree download destination paths

make_SNPtree_urls(): generate ftp site download urls for all SNP trees containing the provided isolates

make_dest_paths(): Make download destination paths

make_download_urls(): make specific ftp download paths for a dataframe with ftp_paths and assembly accessions

make_ftp_paths(): generate ftp site paths for a selection of assembly accessions

mark_outliers(): Mark outliers from a distance matrix

pick_derep_sets(): Pick multiple de-replication sets from a pangenome, uses furrr::future_map Be sure to set your 'plan()'!!!

remove_strict_core(): Removes genes present in all genomes from pangenome presence/absence matrix