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Read and process single-cell paired-chain TCR-seq data

read_external_paired.Rd

[Experimental] This function reads and processes paired TCR-sequencing data from a non-TIRTLseq assay. Currently 10X and Parse Biosciences data are supported.

Usage

read_external_paired(
  path,
  format = c("auto", "10X", "ParseBio"),
  id_cols = make_tcr_schema(features = c("v", "j", "cdr3_aa", "cdr3_nt"), second_alpha =
    FALSE),
  multi = FALSE,
  separate_rows = TRUE,
  productive_only = TRUE,
  verbose = TRUE
)

Arguments

path

the path to the data file

format

the format of the data, either "10X" or "ParseBio" or "auto". If "auto" (default), the function will try to decipher which technology the data file was created by.

id_cols

a vector of column names to be used to define a clone (e.g. c("va","vb","ja","jb","alpha_nuc", "beta_nuc", "cdr3a", "cdr3b")). This can be produced automatically using the make_tcr_schema() function.

multi

If FALSE (default), select only the best two alpha chains for each beta chain when processing the data and creating a data frame with paired TCRs. If TRUE, keep all alphas.

separate_rows

If TRUE, when there are multiple alpha chains paired with one beta chain, put each pair in a separate row in the output data frame. If FALSE, add second alpha chain in extra columns on the same row.

productive_only

If TRUE, keep only "productive" chains

verbose

If TRUE, print messages.

Value

A list containing the following slots:

  • df_pairs_complete - (data frame) paired receptors - one row for each receptor (excluding those missing an alpha or beta chain)

  • df_pairs - (data frame) with paired receptors - one row for each receptor (including those missing an alpha or beta chain)

  • df_pairs_long - (data frame) with paired receptors - one row for each cell (including those missing an alpha or beta chain)

  • df_pairs_long_complete - (data frame) with paired receptors - one row for each cell (excluding those missing an alpha or beta chain)

  • df_raw - (data frame) un-edited input data

  • chain_df - (data frame) summary of total number of each chain in input data

  • barcode_df - (data frame) summary of number of chains found in each cell

  • id_cols - (character vector) columns used as IDs to uniquely define receptor pairs

  • n_cells_total -(integer) total number of cells

  • n_cells_complete - (integer) number of cells with both chains

Details

Supported data types:

  • "10X" - "filtered_contig_annotations.csv" or "all_contig_annotations.csv" outputs from Cell Ranger (https://www.10xgenomics.com/support/software/cell-ranger/7.2/analysis/outputs/cr-5p-outputs-overview-vdj)

  • "ParseBio" - "tcr_annotation_airr.tsv" output from Trailmaker

See also

Other data_processing: TIRTL_process(), add_single_chain_data(), clean_pairs(), combine_bulk_and_paired_data(), filter_duplicate_tcrs(), filter_mait(), filter_nonfunctional_TCRs(), filter_short_cdr3s(), filter_v_alleles(), identify_non_functional_seqs(), identify_paired(), make_tcr_schema(), prep_for_tcrdist(), read_external_bulk(), remove_duplicates()