vepInPhenoLevel-methods: VEP predictions of variants observed in samples
In TVTB: TVTB: The VCF Tool Box

Description Usage Arguments Value Note Warning Author(s) See Also Examples

Returns VEP predictions for variants observed (uniquey) in samples associated with a given phenotype level.

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## S4 method for signature 'ExpandedVCF'
vepInPhenoLevel(
    vcf, phenoCol, level, vepCol, unique = FALSE)

`vcf`	`ExpandedVCF` object. `metadata(vcf)[["TVTBparam"]]` must contain a `TVTBparam` object.
`phenoCol`	Name of a column in `pheno`.
`level`	Phenotype level; only variants observed in at least one sample will be considered.
`vepCol`	VEP prediction fields; `character` vector of metadata columns in `ensemblVEP::parseCSQToGRanges(vcf)`.
`unique`	If `TRUE`, consider only variants unique to the phenotype level (i.e. absent from all other phenotype levels).

A GRanges including all VEP predictions associated with a variant seen in at least one sample (heterozygote or alternate homozygote) associated with the phenotype level. The GRanges contains at least one column for the VEP prediction value. Additional columns containing another VEP prediction field may be added using the facet argument.

If available, "Feature" is a recommended value for this argument, as VEP typically produce one prediction per variant per feature.

A warning message is issued if genotypes are not fully defined in the TVTBparam.

Kevin Rue-Albrecht

VCF, ensemblVEP, GRanges, and DataFrame.

# Example data ----

# VCF file
vcfFile <- system.file("extdata", "moderate.vcf", package = "TVTB")

# Phenotype file
phenoFile <- system.file("extdata", "moderate_pheno.txt", package = "TVTB")
phenotypes <- S4Vectors::DataFrame(
    read.table(file = phenoFile, header = TRUE, row.names = 1))

# TVTB parameters
tparam <- TVTBparam(Genotypes("0|0", c("0|1", "1|0"), "1|1"))

# Pre-process variants
vcf <- VariantAnnotation::readVcf(
    vcfFile, param = tparam, colData = phenotypes)
vcf <- VariantAnnotation::expand(vcf, row.names = TRUE)


# Example usage ----

vepInPhenoLevel(vcf, "super_pop", "AFR", c("CADD_PHRED", "Feature", "IMPACT"))