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Read a VCF file into a tidy variant data frame

Source: R/read_vcf.R
read_vcf.Rd

Parses a standard VCF (v4.x) file and returns a tidy data.frame (a gvf object) that all ggvariant plotting functions accept. For users who already have variant data in a plain data.frame or tibble, see coerce_variants().

Usage

read_vcf(path, samples = NULL, pass_only = TRUE, info_fields = NULL)

Arguments

path

Path to a .vcf or .vcf.gz file.

samples

Character vector of sample names to retain. NULL (default) keeps all samples.

pass_only

Logical. If TRUE (default), only variants with FILTER equal to "PASS" or "." are retained.

info_fields

Not yet implemented; passing a non-NULL value aborts with an error. Reserved for future INFO field expansion. See https://github.com/josh45-source/ggvariant/issues/2.

Value

A gvf (genomic variant frame) — a data.frame with columns:

chrom

Chromosome (character)

pos

Position (integer)

ref

Reference allele

alt

Alternate allele (multi-allelic sites are split into rows)

qual

QUAL score (numeric)

filter

FILTER field

sample

Sample name (NA for single-sample VCFs without GT field)

consequence

Variant consequence if ANN/CSQ INFO field is present

gene

Gene symbol if ANN/CSQ INFO field is present

References

Danecek P, Auton A, Abecasis G, et al.; 1000 Genomes Project Analysis Group (2011). The variant call format and VCFtools. Bioinformatics, 27(15), 2156-2158. doi:10.1093/bioinformatics/btr330

Cingolani P, Platts A, Wang LL, et al. (2012). A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly, 6(2), 80-92. doi:10.4161/fly.19695

McLaren W, Gil L, Hunt SE, et al. (2016). The Ensembl Variant Effect Predictor. Genome Biology, 17(1), 122. doi:10.1186/s13059-016-0974-4

See also

coerce_variants(), plot_lollipop(), plot_consequence_summary()

Other ggvariant input: coerce_variants()

Examples

vcf_file <- system.file("extdata", "example.vcf", package = "ggvariant")
variants <- read_vcf(vcf_file)
#> ℹ Reading VCF: example.vcf
#> ✔ Reading VCF: example.vcf [10ms]
#> 
#> Loaded 19 variant records across 7 chromosomes.
head(variants)
#> <gvf: 6 variants, 1 sample, 3 chromosomes, 4 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