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Coerce a plain data frame to a gvf object

Source: R/read_vcf.R
coerce_variants.Rd

If you already have variant data in a data.frame (e.g. exported from Excel, a database, or another tool), use this function to prepare it for use with ggvariant plotting functions.

Usage

coerce_variants(
  x,
  chrom = "chrom",
  pos = "pos",
  ref = "ref",
  alt = "alt",
  consequence = "consequence",
  gene = "gene",
  sample = "sample"
)

Arguments

x

A data.frame or tibble.

chrom

Column name containing chromosome (default "chrom").

pos

Column name containing position (default "pos").

ref

Column name containing reference allele (default "ref").

alt

Column name containing alternate allele (default "alt").

consequence

Column name containing variant consequence annotation, e.g. "Missense_Mutation". If NULL, consequence is inferred from REF/ALT lengths.

gene

Column name containing gene symbol (default "gene").

sample

Column name containing sample identifier (default "sample").

Value

A gvf object.

See also

read_vcf()

Other ggvariant input: read_vcf()

Examples

df <- data.frame(
  chromosome = c("chr1", "chr1", "chr7"),
  position   = c(100200, 100350, 55249071),
  ref_allele = c("A", "G", "C"),
  alt_allele = c("T", "A", "T"),
  variant_class = c("missense_variant", "synonymous_variant", "missense_variant"),
  hugo_symbol = c("GENE1", "GENE1", "EGFR"),
  tumor_sample = c("S1", "S2", "S2")
)

variants <- coerce_variants(df,
  chrom       = "chromosome",
  pos         = "position",
  ref         = "ref_allele",
  alt         = "alt_allele",
  consequence = "variant_class",
  gene        = "hugo_symbol",
  sample      = "tumor_sample"
)