rank_prevalence_ccdb: Rank contigs, per cell, by experiment-wide prevalence of...

In CellaRepertorium: Data structures, clustering and testing for single cell immune receptor repertoires (scRNAseq RepSeq/AIRR-seq)

Description

Rank contigs, per cell, by experiment-wide prevalence of cluster_pk, which is added as the prevalence field

Usage

rank_prevalence_ccdb(
  ccdb,
  contig_filter_args = TRUE,
  tie_break_keys = c("umis", "reads")
)

rank_chain_ccdb(
  ccdb,
  contig_filter_args = TRUE,
  tie_break_keys = c("umis", "reads"),
  chain_key = "chain",
  contig_fields = tie_break_keys,
  chain_levels = c("IGL", "IGK", "TRA", "TRB", "IGH")
)

Arguments

ccdb	ContigCellDB()
contig_filter_args	an expression passed to dplyr::filter(). Unlike filter, multiple criteria must be & together, rather than using commas to separate. These act on ccdb$contig_tbl
tie_break_keys	(optional) character naming fields in contig_tbl that are used sort the contig table in descending order. Used to break ties if contig_filter_args does not return a unique contig for each cluster
chain_key	character naming the field in contig_tbl to be sorted on.
contig_fields	Optional fields from contig_tbl that will be copied into the cluster_tbl from the canonical contig.
chain_levels	an optional character vector providing the sort order of the chain column in tbl. If set to length zero, then the the ordering will be alphabetical

Value

ContigCellDB with modified contig_tbl

Functions

• rank_chain_ccdb: return a canonical contig by chain type, with TRB/IGH returned first. By default, ties are broken by umis and reads.

Examples

data(ccdb_ex)
ccdb_ex = cluster_germline(ccdb_ex)
rank_prev = rank_prevalence_ccdb(ccdb_ex)
rank_prev$contig_tbl
rank_chain = rank_chain_ccdb(ccdb_ex)
rank_chain$contig_tbl

CellaRepertorium documentation built on Nov. 8, 2020, 7:48 p.m.