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Assign clonotypes from raw VDJ contig data

Source: R/clonotype_engine.R
assign_clonotype.Rd

Complete VDJigsaw pipeline that takes raw VDJ contig annotations, pivots them to wide format, validates TCR chains, identifies clonotypes at multiple stringency levels, and returns the annotated data with clone assignments.

Usage

assign_clonotype(
  VDJ_data,
  sample_col = NULL,
  clone_definition_df = .clone.definition.df,
  is_cell = FALSE,
  high_confidence = FALSE,
  productive = FALSE,
  full_length = FALSE,
  remove_invalid_VDJ = FALSE,
  cdr3_col = "cdr3_nt",
  num_cores = 1,
  clone_loose = "single_chain_single_allele",
  verbose = TRUE
)

Arguments

VDJ_data

A data frame of VDJ contig annotations in 10x Genomics format.

sample_col

Name of the column in VDJ_data to use as sample identifier. If NULL, all cells are assigned to "Sample".

clone_definition_df

Clone definition data frame specifying the stringency hierarchy. Defaults to the built-in definition.

is_cell

Logical. If TRUE, filter to rows where is_cell == "true".

high_confidence

Logical. If TRUE, filter to rows where high_confidence == "true".

productive

Logical. If TRUE, filter to rows where productive == "true".

full_length

Logical. If TRUE, filter to rows where full_length == "true".

remove_invalid_VDJ

Logical. If TRUE, set invalid VDJ sequences to NA.

cdr3_col

Which CDR3 column to use for building the composite TCR chain identifier. Either "cdr3_nt" (nucleotide, default) or "cdr3" (amino acid).

num_cores

Number of cores for parallel processing. Set to -1 to use all available cores. Capped at the number of available cores and the number of unique samples.

clone_loose

Which stringency level to use as the default "loose" clone definition.

verbose

Logical. If TRUE, print progress messages.

Value

A list with two elements:

TCR_data

Wide-format data frame with TCR chains, clone IDs at each stringency level, and a default CloneID column.

ref_tables

Named list of reference tables for each stringency level.

Examples

if (FALSE) { # \dontrun{
VDJ_contigs <- read.csv("filtered_contig_annotations.csv")
result <- assign_clonotype(VDJ_contigs, sample_col = "origin")
TCR_data <- result$TCR_data
ref_tables <- result$ref_tables
} # }