VCF-class {VariantAnnotation} | R Documentation

## VCF class objects

### Description

The VCF class is a virtual class extended from `RangedSummarizedExperiment`. The subclasses, `CompressedVCF` and `ExtendedVCF`, are containers for holding data from Variant Call Format files.

### Details

The `VCF` class is a virtual class with two concrete subclasses, `CollapsedVCF` and `ExtendedVCF`.

Slots unique to `VCF` and subclasses,

- `fixed`: A DataFrame containing the REF, ALT, QUAL and FILTER fields from a VCF file.

- `info`: A DataFrame containing the INFO fields from a VCF file.

Slots inherited from `RangedSummarizedExperiment`,

- `metadata`: A `list` containing the file header or other information about the overall experiment.

- `rowRanges`: A GRanges-class instance defining the variant ranges and associated metadata columns of REF, ALT, QUAL and FILTER.

- `colData`: A DataFrame-class instance describing the samples and associated metadata.

- `geno`: The `assays` slot from `RangedSummarizedExperiment` has been renamed as `geno` for the VCF class. This slot contains the genotype information immediately following the FORMAT field in a VCF file. Each element of the `list` or `SimpleList` is a matrix or array.

It is expected that users will not create instances of the VCF class but instead one of the concrete subclasses, CollapsedVCF or ExpandVCF. CollapsedVCF contains the ALT data as a `DNAStringSetList` allowing for multiple alleles per variant. The ExpandedVCF ALT data is a `DNAStringSet` where the ALT column has been expanded to create a flat form of the data with one row per variant-allele combination. In the case of strucutral variants, ALT will be a `CompressedCharacterList` or `character` in the collapsed or expanded forms.

### Constructors

  `readVcf(file, genome, param, ..., row.names=TRUE)`

  `VCF(rowRanges = GRanges(), colData = DataFrame(), exptData = list(header = VCFHeader()), fixed = DataFrame(), info = DataFrame(), geno = SimpleList(), ..., collapsed=TRUE, verbose = FALSE)` Creates CollapsedVCF when `collapsed = TRUE` and an ExpandedVCF when `collapsed = FALSE`.

  This is a low-level constructor used internally. Most instances of the `VCF` are created with `readVcf`.

### Accessors

In the following code snippets `x` is a CollapsedVCF or ExpandedVCF object.

  `rowRanges(x, ..., fixed = TRUE)`, `rowRanges(x) <- value`: Gets or sets the rowRanges. The CHROM, POS, ID, POS and REF fields are used to create a `GRanges` object. The start of the ranges are defined by POS and the width is equal to the width of the reference allele REF. The IDs become the rownames. If they are missing (i.e., ‘.’) a string of CHROM:POS_REF/ALT is used instead. The `genome` argument is stored in the seqinfo of the `GRanges` and can be accessed with `genome(<VCF>)`.

  When `fixed = TRUE`, REF, ALT, QUAL and FILTER metadata columns are displayed as metadata columns. To modify the `fixed` fields, use the `fixed<-` setter.

  One metadata column, `paramRangeID`, is included with the `rowRanges`. This ID is meaningful when multiple ranges are specified in the `ScanVcfParam` and distinguishes which records match each range.

  The metadata columns of a VCF object are accessed with the following:

  - `ref(x)`, `ref(x) <- value`: Gets or sets the reference allele (REF). `value` must be a `DNAStringSet`.

  - `alt(x)`, `alt(x) <- value`: Gets or sets the alternate allele data (ALT). When `x` is a CollapsedVCF, `value` must be a `DNAStringSetList` or `CompressedCharacterList`. For ExpandedVCF, `value` must be a `DNAStringSet` or `character`.

  - `qual(x)`, `qual(x) <- value`: Returns or sets the quality scores (QUAL). `value` must be an `numeric(1L)`.

  - `filt(x)`, `filt(x) <- value`: Returns or sets the filter data. `value` must be a `character(1L)`. Names must be one of 'REF', 'ALT', 'QUAL' or 'FILTER'.

  `mcols(x)`, `mcols(x) <- value`: These methods behave the same as `mcols(rowRanges(x))` and `mcols(rowRanges(x)) <- value`. This method does not manage the fixed fields, 'REF', 'ALT', 'QUAL' or 'FILTER'. To modify those columns use `fixed<-`.

  `fixed(x)`, `fixed(x) <- value`: Gets or sets a DataFrame of REF, ALT, QUAL and FILTER only. Note these fields are displayed as metadata columns with the rowRanges() data (set to fixed = FALSE to suppress).

  `info(x, ..., row.names = TRUE)`, `info(x) <- value`: Gets or sets a DataFrame of INFO variables. Row names are added if unique and `row.names=TRUE`.

  `geno(x, withDimnames=TRUE)`, `geno(x) <- value`: Gets a SimpleList of genotype data. `value` is a SimpleList. To replace a single variable in the SimpleList use `geno(x)$variable <- value`; in this case `value` must be a matrix or array. By default row names are returned; to override specify `geno(vcf, withDimnames=FALSE)`.

  `metadata(x)`: Gets a `list` of experiment-related data. By default this list includes the ‘header’ information from the VCF file. See the use of `header()` for details in extracting header information.

  `colData(x)`, `colData(x) <- value`: Gets or sets a `DataFrame` of sample-specific information. Each row represents a sample in the VCF file. `value` must be a `DataFrame` with rownames representing the samples in the VCF file.

  `genome(x)`: Extract the `genome` information from the `GRanges` object returned by the `rowRanges` accessor.

  `seqlevels(x)`: Extract the `seqlevels` from the `GRanges` object returned by the `rowRanges` accessor.

  `strand(x)`: Extract the `strand` from the `GRanges` object returned by the `rowRanges` accessor.

  `header(x)`, `header(x)<- value`: Get or set the VCF header information. Replacement value must be a `VCFHeader` object. To modify individual elements use `info<-`, `geno<-` or `meta<-` on a ‘VCFHeader’ object. See ?`VCFHeader` man page for details.

  - `info(header(x))`

  - `geno(header(x))`

  - `meta(header(x))`

  - `samples(header(x))`

### Subsetting and combining

In the following code `x` is a VCF object, and ... is a list of VCF objects.

  `x[i, j]`, `x[i, j] <- value`: Gets or sets rows and columns. `i` and `j` can be integer or logical vectors. `value` is a replacement `VCF` object.

  `subset(x, subset, select, ...)`: Restricts `x` by evaluating the `subset` argument in the scope of `rowData(x)` and `info(x)`, and `select` in the context of `colData(x)`. The `subset` argument restricts by rows, while the `select` argument restricts by column. The `...` are passed to the underlying `subset()` calls.

  `cbind(...)`, `rbind(...)`: `cbind` combines objects with identical ranges (`rowRanges`) but different samples (columns in `assays`). The colnames in `colData` must match or an error is thrown. Columns with duplicate names in `fixed`, `info` and `mcols(rowRanges(VCF))` must contain the same data.

  `rbind` combines objects with different ranges (`rowRanges`) and the same subjects (columns in `assays`). Columns with duplicate names in `colData` must contain the same data. The ‘Samples’ columns in `colData` (created by `readVcf`) are renamed with a numeric extension ordered as they were input to `rbind` e.g., “Samples.1, Samples.2, ...” etc.

  `metadata` from all objects are combined into a `list` with no name checking.

### expand

In the following code snippets `x` is a CollapsedVCF object.

  `expand(x, ..., row.names = FALSE)`: Expand (unlist) the ALT column of a CollapsedVCF object to one row per ALT value. Variables with Number='A' have one value per alternate allele and are expanded accordingly. The 'AD' genotype field is expanded into REF/ALT pairs. For all other fields, the rows are replicated to match the elementNROWS of ALT.

  The output is an ExpandedVCF with ALT as a `DNAStringSet` or `character` (structural variants). By default rownames are NULL. When `row.names=TRUE` the expanded output has duplicated rownames corresponding to the original `x`.

### genotypeCodesToNucleotides(vcf, ...)

This function converts the 'GT' genotype codes in a `VCF` object to nucleotides. See also ?`readGT` to read in only 'GT' data as codes or nucleotides.

### SnpMatrixToVCF(from, seqSource)

This function converts the output from the read.plink function to a `VCF` class. `from` must be a list of length 3 with named elements "map", "fam" and "genotypes". `seqSource` can be a `BSgenome` or an FaFile used for reference sequence extraction.

### Variant Type

Functions to identify variant type include isSNV, isInsertion, isDeletion, isIndel, isSubstitution and isTransition. See the ?`isSNV` man page for details.

### Arguments

geno

  A `list` or `SimpleList` of matrix elements, or a `matrix` containing the genotype information from a VCF file. If present, these data immediately follow the FORMAT field in the VCF.

  Each element of the list must have the same dimensions, and dimension names (if present) must be consistent across elements and with the row names of `rowRanges`, `colData`.

info

  A `DataFrame` of data from the INFO field of a VCF file. The number of rows must match that in the `rowRanges` object.

fixed

  A `DataFrame` of REF, ALT, QUAL and FILTER fields from a VCF file. The number of rows must match that of the `rowRanges` object.

rowRanges

  A `GRanges` instance describing the ranges of interest. Row names, if present, become the row names of the `VCF`. The length of the `GRanges` must equal the number of rows of the matrices in `geno`.

colData

  A `DataFrame` describing the samples. Row names, if present, become the column names of the `VCF`.

metadata

  A `list` describing the header of the VCF file or additional information for the overall experiment.

...

  For `cbind` and `rbind` a list of VCF objects. For all other methods ... are additional arguments passed to methods.

collapsed

  A `logical(1)` indicating whether a CollapsedVCF or ExpandedVCF should be created. The ALT in a CollapsedVCF is a `DNAStringSetList` while in a ExpandedVCF it is a `DNAStringSet`.

verbose

  A `logical(1)` indicating whether messages about data coercion during construction should be printed.

### Author(s)

Valerie Obenchain

### See Also

GRanges, DataFrame, SimpleList, RangedSummarizedExperiment, `readVcf`, `writeVcf` `isSNV`

### Examples

    ## readVcf() parses data into a VCF object:

    fl <- system.file("extdata", "structural.vcf", package="VariantAnnotation")
    vcf <- readVcf(fl, genome="hg19")

    ## ----------------------------------------------------------------
    ## Accessors
    ## ----------------------------------------------------------------
    ## Variant locations are stored in the GRanges object returned by
    ## the rowRanges() accessor.
    rowRanges(vcf)

    ## Suppress fixed fields:
    rowRanges(vcf, fixed=FALSE)

    ## Individual fields can be extracted with ref(), alt(), qual(), filt() etc.
    qual(vcf)
    ref(vcf)
    head(info(vcf))

    ## Extract genotype fields with geno(). Access specific fields with
    ## '$' or '[['.
    geno(vcf)
    identical(geno(vcf)$GQ, geno(vcf)[[2]])

    ## ----------------------------------------------------------------
    ## Renaming seqlevels and subsetting
    ## ----------------------------------------------------------------
    ## Overlap and matching operations require that the objects
    ## being compared have the same seqlevels (chromosome names).
    ## It is often the case that the seqlevesls in on of the objects
    ## needs to be modified to match the other. In this VCF, the
    ## seqlevels are numbers instead of preceded by "chr" or "ch".

    seqlevels(vcf)

    ## Rename the seqlevels to start with 'chr'.
    vcf2 <- renameSeqlevels(vcf, paste0("chr", seqlevels(vcf)))
    seqlevels(vcf2)

    ## The VCF can also be subset by seqlevel using 'keepSeqlevels'
    ## or 'dropSeqlevels'. See ?keepSeqlevels for details.
    vcf3 <- keepSeqlevels(vcf2, "chr2", pruning.mode="coarse")
    seqlevels(vcf3)

    ## ----------------------------------------------------------------
    ## Header information
    ## ----------------------------------------------------------------

    ## Header data can be modified in the 'meta', 'info' and 'geno'
    ## slots of the VCFHeader object. See ?VCFHeader for details.

    ## Current 'info' fields.
    rownames(info(header(vcf)))

    ## Add a new field to the header.
    newInfo <- DataFrame(Number=1, Type="Integer",
                         Description="Number of Samples With Data",
                         row.names="NS")
    info(header(vcf)) <- rbind(info(header(vcf)), newInfo)
    rownames(info(header(vcf)))

    ## ----------------------------------------------------------------
    ## Collapsed and Expanded VCF
    ## ----------------------------------------------------------------
    ## readVCF() produces a CollapsedVCF object.
    fl <- system.file("extdata", "ex2.vcf",
                      package="VariantAnnotation")
    vcf <- readVcf(fl, genome="hg19")
    vcf

    ## The ALT column is a DNAStringSetList to allow for more
    ## than one alternate allele per variant.
    alt(vcf)

    ## For structural variants ALT is a CharacterList.
    fl <- system.file("extdata", "structural.vcf",
                      package="VariantAnnotation")
    vcf <- readVcf(fl, genome="hg19")
    alt(vcf)

    ## ExpandedVCF is the 'flattened' counterpart of CollapsedVCF.
    ## The ALT and all variables with Number='A' in the header are
    ## expanded to one row per alternate allele.
    vcfLong <- expand(vcf)
    alt(vcfLong)

    ## Also see the ?VRanges class for an alternative form of
    ## 'flattened' VCF data.

    ## ----------------------------------------------------------------
    ## isSNV()
    ## ----------------------------------------------------------------
    ## isSNV() returns a subset VCF containing SNVs only.

    vcf <- VCF(rowRanges = GRanges("chr1", IRanges(1:4*3, width=c(1, 2, 1, 1))))
    alt(vcf) <- DNAStringSetList("A", c("TT"), c("G", "A"), c("TT", "C"))
    ref(vcf) <- DNAStringSet(c("G", c("AA"), "T", "G"))
    fixed(vcf)[c("REF", "ALT")]

    ## SNVs are present in rows 1 (single ALT value), 3 (both ALT values)
    ## and 4 (1 of the 2 ALT values).
    vcf[isSNV(vcf, singleAltOnly=TRUE)]
    vcf[isSNV(vcf, singleAltOnly=FALSE)] ## all 3 SNVs

[Package VariantAnnotation version 1.24.5 Index]