print.gvf() shows a compact header (variant / sample / chromosome /
gene counts) followed by a truncated preview, rather than dumping the
full underlying data.frame. summary.gvf() returns consequence,
per-sample, and per-chromosome breakdowns as a summary.gvf object,
printed via its own method.
Examples
vcf_file <- system.file("extdata", "example.vcf", package = "ggvariant")
variants <- read_vcf(vcf_file)
#> ℹ Reading VCF: example.vcf
#> ✔ Reading VCF: example.vcf [15ms]
#>
#> Loaded 19 variant records across 7 chromosomes.
variants
#> <gvf: 19 variants, 2 samples, 7 chromosomes, 8 genes>
#> chrom pos ref alt qual filter consequence gene sample
#> 1 chr17 7577120 C T 250 PASS missense_variant TP53 TUMOR_S1
#> 3 chr17 7578210 G T 95 PASS stop_gained TP53 TUMOR_S1
#> 4 chr17 7579472 A G 310 PASS synonymous_variant TP53 TUMOR_S1
#> 6 chr13 32914437 G A 175 PASS frameshift_variant BRCA2 TUMOR_S1
#> 7 chr17 41244000 AT A 310 PASS frameshift_variant BRCA1 TUMOR_S1
#> 9 chr7 55242465 C A 90 PASS synonymous_variant EGFR TUMOR_S1
#> # ... 13 more rows
summary(variants)
#> gvf summary: 19 variants
#>
#> Consequence breakdown:
#>
#> missense_variant frameshift_variant stop_gained splice_site_variant
#> 9 3 3 2
#> synonymous_variant
#> 2
#>
#> Per-sample counts:
#>
#> TUMOR_S1 TUMOR_S2
#> 10 9
#>
#> Chromosome distribution:
#>
#> chr17 chr12 chr13 chr3 chr7 chr9 chr10
#> 7 3 2 2 2 2 1
