This function removes all non-SNVs mutations, re-creating a new CNAqc object with just SNVs. All analyses are lost.
A CNAqc object.
What reference alleles to use, default c("A", "C", "T", "G").
What alternative alleles to use, default c("A", "C", "T", "G").
A new CNAqc dataset created with init.
data('example_dataset_CNAqc', package = 'CNAqc')
x = init(mutations = example_dataset_CNAqc$mutations, cna = example_dataset_CNAqc$cna, purity = example_dataset_CNAqc$purity)
#>
#> ── CNAqc - CNA Quality Check ───────────────────────────────────────────────────
#>
#> ℹ Using reference genome coordinates for: GRCh38.
#> ✔ Found annotated driver mutations: TTN, CTCF, and TP53.
#> ✔ Fortified calls for 12963 somatic mutations: 12963 SNVs (100%) and 0 indels.
#> ! CNAs have no CCF, assuming clonal CNAs (CCF = 1).
#> ✔ Fortified CNAs for 267 segments: 267 clonal and 0 subclonal.
#> ✔ 12963 mutations mapped to clonal CNAs.
subset_snvs(x)
#> ── [ CNAqc ] MySample 12963 mutations in 267 segments (267 clonal, 0 subclonal).
#>
#> ── Clonal CNAs
#>
#> 2:2 [n = 7478, L = 1483 Mb] ■■■■■■■■■■■■■■■■■■■■■■■■■■■ { CTCF }
#> 4:2 [n = 1893, L = 331 Mb] ■■■■■■■
#> 3:2 [n = 1625, L = 357 Mb] ■■■■■■
#> 2:1 [n = 1563, L = 420 Mb] ■■■■■■ { TTN }
#> 3:0 [n = 312, L = 137 Mb] ■
#> 2:0 [n = 81, L = 39 Mb] { TP53 }
#> 16:2 [n = 4, L = 0 Mb]
#> 25:2 [n = 2, L = 1 Mb]
#> 3:1 [n = 2, L = 1 Mb]
#> 106:1 [n = 1, L = 0 Mb]
#>
#> ℹ Sample Purity: 89% ~ Ploidy: 4.
#>
#> ℹ There are 3 annotated driver(s) mapped to clonal CNAs.
#> chr from to ref alt DP NV VAF driver_label is_driver
#> chr2 179431633 179431634 C T 117 77 0.6581197 TTN TRUE
#> chr16 67646006 67646007 C T 120 54 0.4500000 CTCF TRUE
#> chr17 7577106 7577107 G C 84 78 0.9285714 TP53 TRUE