mutate_vdj: Modify V(D)J data in object

In rnabioco/AVIDtools: A collection of single-cell V(D)J tools

Modify V(D)J data in object

Description

Modify per-chain V(D)J data for each cell. This function offers greater flexibility than summarize_vdj(), but is less user-friendly.

Usage

mutate_vdj(
  input,
  ...,
  clonotype_col = global$clonotype_col,
  data_cols = NULL,
  return_df = FALSE,
  sep = global$sep
)

Arguments

input	Single cell object or data.frame containing V(D)J data. If a data.frame is provided, cell barcodes should be stored as row names.
...	Name-value pairs to use for creating or modifying per-chain V(D)J meta.data, e.g. mean_umis = mean(umis). To allow for modification of per-chain V(D)J data, the data for each cell is converted into a vector, e.g. 'IGH;IGK' is equivalent to c('IGH', 'IGK'). This allows R vector operations to be performed on the per-chain values. Any operations that produce a result greater than length 1 need to be returned as a list(), e.g. new_col = umis + 1 will return a new value for each chain, to prevent an error this must be written as new_col = list(umis + 1).
clonotype_col	meta.data column containing clonotype IDs. This is used to identify columns containing V(D)J data.
data_cols	meta.data columns containing V(D)J data to modify. If NULL, data are automatically selected by identifying columns that have NAs in the same rows as clonotype_col.
return_df	Return results as a data.frame. If FALSE, results will be added to the input object.
sep	Separator used for storing per cell V(D)J data. If NULL, columns containing V(D)J data will not be converted to vectors for filtering.

Value

Object with modified meta.data

Examples

# Calculate mean reads and UMIs per cell
res <- mutate_vdj(
  vdj_sce,
  mean_umis  = mean(umis),
  mean_reads = mean(reads)
)

head(slot(res, "colData"), 3)

# Calculate the total number of insertions + deletions for each chain
# we have to wrap our expression in list() since a value is returned for
# each chain
res <- mutate_vdj(
  vdj_sce,
  indels = list(all_ins + all_del)
)

head(slot(res, "colData"), 3)

# Create a new column showing the unique chains for each cell
res <- mutate_vdj(
  vdj_sce,
  unique_chains = stringr::str_c(unique(chains), collapse = "_")
)

head(slot(res, "colData"), 3)

# Determine which cells have both an IGK and IGL chain
res <- mutate_vdj(
  vdj_sce,
  both_light = all(c("IGK", "IGL") %in% chains)
)

head(slot(res, "colData"), 1)

# Determine which cells have multiple light chains
res <- mutate_vdj(
  vdj_sce,
  multi_light = sum(chains %in% c("IGK", "IGL")) > 1
)

head(slot(res, "colData"), 3)

rnabioco/AVIDtools documentation built on Oct. 28, 2023, 10:23 a.m.