Modification to members will trigger various forms of equalization. See equalize_ccdb() for details.

# S4 method for ContigCellDB
$(x, name)

# S4 method for ContigCellDB
$(x, name) <- value

Arguments

x

A ContigCellDB object

name

a slot of a ContigCellDB object (one of c('contig_tbl', 'cell_tbl', 'contig_pk', 'cell_pk', 'cluster_tbl', 'cluster_pk'))

value

The value assigned to a slot of ContigCellDB object

Value

Update or return a slot of ContigCellDB()

See also

Examples

data(ccdb_ex)
ccdb_ex$contig_tbl
#> # A tibble: 1,508 × 22
#>    anno_file pop   sample barcode is_cell contig_id high_confidence length chain
#>    <chr>     <chr> <chr>  <chr>   <lgl>   <chr>     <lgl>            <dbl> <chr>
#>  1 /Users/a… b6    4      AAAGTA… TRUE    AAAGTAGT… TRUE               611 TRB  
#>  2 /Users/a… b6    4      AAAGTA… TRUE    AAAGTAGT… TRUE               609 TRB  
#>  3 /Users/a… b6    4      AAAGTA… TRUE    AAAGTAGT… TRUE               538 TRA  
#>  4 /Users/a… b6    4      AACCAT… TRUE    AACCATGC… TRUE               799 TRA  
#>  5 /Users/a… b6    4      AACTGG… TRUE    AACTGGTG… TRUE               634 TRB  
#>  6 /Users/a… b6    4      AACTGG… TRUE    AACTGGTG… TRUE               923 TRA  
#>  7 /Users/a… b6    4      AAGCCG… TRUE    AAGCCGCA… TRUE               693 TRB  
#>  8 /Users/a… b6    4      AAGTCT… TRUE    AAGTCTGG… TRUE               658 TRB  
#>  9 /Users/a… b6    4      AAGTCT… TRUE    AAGTCTGG… TRUE               558 TRA  
#> 10 /Users/a… b6    4      ACACCA… TRUE    ACACCAAA… TRUE               614 TRB  
#> # … with 1,498 more rows, and 13 more variables: v_gene <chr>, d_gene <chr>,
#> #   j_gene <chr>, c_gene <chr>, full_length <lgl>, productive <chr>,
#> #   cdr3 <chr>, cdr3_nt <chr>, reads <dbl>, umis <dbl>, raw_clonotype_id <chr>,
#> #   raw_consensus_id <chr>, celltype <chr>
ccdb_ex$cell_tbl
#> # A tibble: 832 × 3
#>    pop   sample barcode           
#>    <chr> <chr>  <chr>             
#>  1 b6    4      AAAGTAGTCGCGCCAA-1
#>  2 b6    4      AACCATGCATTTGCCC-1
#>  3 b6    4      AACTGGTGTCTGATCA-1
#>  4 b6    4      AAGCCGCAGTAAGTAC-1
#>  5 b6    4      AAGTCTGGTTCAACCA-1
#>  6 b6    4      ACACCAAAGTCCAGGA-1
#>  7 b6    4      ACATGGTAGTGTTTGC-1
#>  8 b6    4      ACCCACTTCCACGACG-1
#>  9 b6    4      ACGCCAGGTCCGAATT-1
#> 10 b6    4      ACGCCAGTCCAATGGT-1
#> # … with 822 more rows
ccdb_ex$cluster_tbl
#> # A tibble: 0 × 0
data(ccdb_ex)
ccdb_ex$contig_pk = c("sample","barcode","contig_id") # 'pop' is technically redundant with 'sample'
# Take a subset of ccdb_ex
ccdb_ex
#> ContigCellDB of 1508 contigs; 832 cells; and 0 clusters.
#> Contigs keyed by sample, barcode, contig_id; cells keyed by pop, sample, barcode.
ccdb_ex$contig_tbl = dplyr::filter(ccdb_ex$contig_tbl, pop == 'b6')
ccdb_ex
#> ContigCellDB of 767 contigs; 832 cells; and 0 clusters.
#> Contigs keyed by sample, barcode, contig_id; cells keyed by pop, sample, barcode.