Example CNAqc dataset.
data(example_dataset_CNAqc)A list of SNVs, allele-specific copy number alterations (CNAs) and purity value that can be used with CNAqc. This tumour does not contain subclonal CNAs.
data(example_dataset_CNAqc)
example_dataset_CNAqc
#> $mutations
#> # A tibble: 12,963 × 13
#> chr from to ref alt FILTER DP NV VAF ANNOVAR_FUNCTION
#> <chr> <dbl> <dbl> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
#> 1 chr1 1027104 1027105 T G PASS 60 6 0.1 UTR5
#> 2 chr1 2248588 2248589 A C PASS 127 9 0.0709 intergenic
#> 3 chr1 2461999 2462000 G A PASS 156 65 0.417 upstream
#> 4 chr1 2727935 2727936 T C PASS 180 90 0.5 downstream
#> 5 chr1 2763397 2763398 C T PASS 183 61 0.333 intergenic
#> 6 chr1 2768208 2768209 C T PASS 203 130 0.640 intergenic
#> 7 chr1 2935590 2935591 C T PASS 228 132 0.579 intergenic
#> 8 chr1 2980032 2980033 C T PASS 196 85 0.434 ncRNA_exonic
#> 9 chr1 3387161 3387162 T G PASS 124 6 0.0484 intronic
#> 10 chr1 3502517 3502518 G A PASS 88 10 0.114 intronic
#> # ℹ 12,953 more rows
#> # ℹ 3 more variables: GENE <chr>, is_driver <lgl>, driver_label <chr>
#>
#> $cna
#> # A tibble: 267 × 7
#> chr from to length covRatio Major minor
#> <chr> <int> <int> <int> <dbl> <dbl> <dbl>
#> 1 chr1 840009 1689987 849979 1.19 3 2
#> 2 chr1 1689988 1815015 125028 1.26 3 2
#> 3 chr1 1815016 9799969 7984954 1.19 3 2
#> 4 chr1 10479910 12079917 1600008 1.19 3 2
#> 5 chr1 12079917 12154980 75064 1.24 3 2
#> 6 chr1 12154981 12839977 684997 1.19 3 2
#> 7 chr1 13780016 17790026 4010011 1.19 3 2
#> 8 chr1 17849962 21080067 3230106 1.19 3 2
#> 9 chr1 21080068 21559998 479931 1.26 3 2
#> 10 chr1 21559998 24830001 3270004 1.19 3 2
#> # ℹ 257 more rows
#>
#> $purity
#> [1] 0.89
#>
#> $reference
#> [1] "hg19"
#>