Preprocessing: pp

assign_isotype(fasta[, org, evalue, ...])	Annotate contigs with constant region call using blastn.
assign_isotypes(fastas[, org, evalue, ...])	Annotate contigs with constant region call using blastn.
check_contigs(data[, adata, ...])	Check contigs for whether they can be considered as ambiguous or not.
create_germlines(vdj_data[, germline, org, ...])	Run CreateGermlines.py to reconstruct the germline V(D)J sequence.
filter_contigs(*args, **kwargs)	Deprecate function
format_fasta(fasta[, prefix, suffix, sep, ...])	Add prefix to the headers/contig ids in input fasta and annotation file.
format_fastas(fastas[, prefix, suffix, sep, ...])	Add prefix to the headers/contig ids in input fasta and annotation file.
reannotate_genes(data[, igblast_db, ...])	Reannotate cellranger fasta files with igblastn and parses to airr format.
reassign_alleles(data, combined_folder[, ...])	Correct allele calls based on a personalized genotype using tigger.

Tools: tl

transfer(adata, dandelion[, expanded_only, ...])
find_clones(vdj_data[, identity, key, ...])	Find clones based on VDJ chain and VJ chain CDR3 junction hamming distance.
define_clones(vdj_data[, dist, action, ...])	Find clones using changeo's DefineClones.py.
generate_network(vdj_data[, key, clone_key, ...])	Generate a Levenshtein distance network based on full length VDJ sequence alignments for heavy and light chain(s).
clone_centrality(vdj_data)	Calculate node closeness centrality in BCR/TCR network.
clone_degree(vdj_data[, weight])	Calculate node degree in BCR/TCR network.
clone_diversity(vdj_data, groupby[, method, ...])	Compute B cell clones diversity : Gini indices, Chao1 estimates, or Shannon entropy.
clone_overlap(vdj_data, groupby[, ...])	A function to tabulate clonal overlap for input as a circos-style plot.
clone_rarefaction(vdj_data, groupby[, ...])	Return rarefaction predictions for cell numbers vs clone size.
clone_size(vdj_data[, max_size, clone_key, ...])	Quantify size of clones.
extract_edge_weights(vdj_data[, expanded_only])	Retrieve edge weights (BCR levenshtein distance) from graph.
productive_ratio(adata, vdj, groupby[, ...])	Compute the cell-level productive/non-productive contig ratio.
vj_usage_pca(adata, groupby[, min_size, ...])	Extract productive V/J gene usage from single cell data and compute PCA.
setup_vdj_pseudobulk(adata[, mode, ...])	Function for prepare anndata for computing pseudobulk vdj feature space.
vdj_pseudobulk(adata[, pbs, obs_to_bulk, ...])	Function for making pseudobulk vdj feature space.
pseudobulk_gex(adata_raw[, pbs, ...])	Function to pseudobulk gene expression (raw count).
pseudotime_transfer(adata, pr_res[, suffix])	Function to add pseudotime and branch probabilities into adata.obs in place.
project_pseudotime_to_cell(adata, pb_adata, ...)	Function to project pseudotime & branch probabilities from pb_adata (pseudobulk adata) to adata (cell adata).
bin_expression(adata, bin_no, genes, ...)	Function to compute average gene expression in bins along pseudotime.
chatterjee_corr(adata, genes, pseudotime_col)	Function to compute chatterjee correlation of gene expression with pseudotime.

Plotting: pl

barplot(vdj_data, color[, palette, figsize, ...])	A barplot function to plot usage of V/J genes in the data.
clone_network(adata[, basis, edges])	Using scanpy's plotting module to plot the network.
clone_overlap(adata, groupby[, colorby, ...])	A plot function to visualise clonal overlap as a circos-style plot.
clone_rarefaction(vdj_data, color[, ...])	Plot rarefaction curve for cell numbers vs clone size.
productive_ratio(adata[, figsize, palette, ...])	Plot productive/non-productive contig ratio from AnnData (cell level).
spectratype(vdj_data, color, groupby, locus)	A spectratype function to plot usage of CDR3 length.
stackedbarplot(vdj_data, color, groupby[, ...])	A stacked bar plot function to plot usage of V/J genes in the data split by groups.

Utilities: utl

concat(arrays[, check_unique, sep, ...])	Concatenate data frames and return as Dandelion object.
load_data(obj)	Read in or copy dataframe object and set sequence_id as index without dropping.
read_h5ddl([filename])	Read in and returns a Dandelion class from .h5ddl format.
read_pkl([filename])	Read in and returns a Dandelion class saved using pickle format.
read_airr(file[, prefix, suffix, sep, ...])	Reads a standard single-cell AIRR rearrangement file.
read_10x_airr(file[, prefix, suffix, sep, ...])	Read the airr_rearrangement.tsv produced from Cell Ranger directly and returns a Dandelion object.
read_10x_vdj(path[, filename_prefix, ...])	A parser to read .csv and .json files directly from folder containing 10x cellranger-outputs.
read_parse_airr(file[, prefix, suffix, sep, ...])	Read the TCR or BCR _annotation_airr.tsv produced from Parse Biosciences Evercode technology.
read_bd_airr(file[, prefix, suffix, sep, ...])	Read the TCR or BCR _AIRR.tsv produced from BD Rhapsody technology.
to_scirpy(data[, transfer, to_mudata, ...])	Convert Dandelion data to scirpy-compatible format.
from_scirpy(data)	Convert data from scirpy format to Dandelion format.
makeblastdb(ref)	Run makeblastdb on constant region fasta file.

Dandelion

Dandelion([data, metadata, germline, ...])

Dandelion class object.

dandelion.Dandelion

add_cell_prefix(prefix[, sync, ...])	Add prefix to cell_id and optionally to sequence_id.
add_cell_suffix(suffix[, sync, ...])	Add prefix to cell_id and optionally to sequence_id.
add_sequence_prefix(prefix[, sync, ...])	Add prefix to sequence_id and then apply to cell_id as well.
add_sequence_suffix(suffix[, sync, ...])	Add suffix to sequence_id and then apply to cell_id as well.
copy()	Performs a deep copy of all slots in Dandelion class.
reset_ids()	Reset both IDs to their original values.
simplify(**kwargs)	Disambiguate VDJ and C gene calls when there's multiple calls separated by commas and strip the alleles.
store_germline_reference([corrected, ...])	Update germline reference with corrected sequences and store in Dandelion object.
update_metadata([retrieve, clone_key, ...])	A Dandelion initialisation function to update and populate the .metadata slot.
update_plus([option])	Retrieve additional data columns that are useful.
write([filename, compression, ...])	Writes a Dandelion class to .h5ddl format.
write_10x([folder, filename_prefix, ...])	Writes a Dandelion class to 10x formatted files so that it can be ingested for other tools.
write_airr([filename])	Writes a Dandelion class to AIRR formatted .tsv format.
write_h5ddl([filename, compression, ...])	Writes a Dandelion class to .h5ddl format.
write_pkl([filename])	Writes a Dandelion class to .pkl format.

Logging

print_header([dependencies])	Versions that are essential for dandelion's operation.
print_versions([dependencies])	Versions that are essential for dandelion's operation.

External

scanpy

recipe_scanpy_qc(adata[, layer, ...])

Recipe for running a standard scanpy QC workflow.

Immmcantation

Wrappers for tools in Immcantation pipeline.

changeo

assigngenes_igblast(fasta[, igblast_db, ...])	Reannotate with IgBLASTn.
creategermlines(airr_file[, germline, org, ...])	Wrapper for CreateGermlines.py for reconstructing germline sequences.
makedb_igblast(fasta[, igblast_output, ...])	Parse IgBLAST output to AIRR format.
parsedb_heavy(airr_file)	Parse AIRR tsv file (heavy chain contigs only).
parsedb_light(airr_file)	Parse AIRR tsv file (light chain contigs only).

tigger

tigger_genotype(airr_file[, v_germline, ...])

Reassign alleles with TIgGER in R.

shazam

calculate_threshold(data[, mode, ...])	Calculating nearest neighbor distances for tuning clonal assignment with shazam.
quantify_mutations(data[, split_locus, ...])	Run basic mutation load analysis.

scoper

identical_clones(vdj_data[, method, ...])	Clonal assignment using sequence identity partitioning.
hierarchical_clones(vdj_data, threshold[, ...])	Hierarchical clustering approach to clonal assignment.
spectral_clones(vdj_data[, method, ...])	Spectral clustering method for clonal partitioning.