summarizeVariants {VariantAnnotation} | R Documentation

## Summarize variants by sample

### Description

Variants in a VCF file are overlapped with an annotation region and summarized by sample. Genotype information in the VCF is used to determine which samples express each variant.

### Usage

    ## S4 method for signature 'TxDb,VCF,CodingVariants'
    summarizeVariants(query, subject, mode, ...)
    ## S4 method for signature 'TxDb,VCF,FiveUTRVariants'
    summarizeVariants(query, subject, mode, ...)
    ## S4 method for signature 'TxDb,VCF,ThreeUTRVariants'
    summarizeVariants(query, subject, mode, ...)
    ## S4 method for signature 'TxDb,VCF,SpliceSiteVariants'
    summarizeVariants(query, subject, mode, ...)
    ## S4 method for signature 'TxDb,VCF,IntronVariants'
    summarizeVariants(query, subject, mode, ...)
    ## S4 method for signature 'TxDb,VCF,PromoterVariants'
    summarizeVariants(query, subject, mode, ...)
    ## S4 method for signature 'GRangesList,VCF,VariantType'
    summarizeVariants(query, subject, mode, ...)
    ## S4 method for signature 'GRangesList,VCF,function'
    summarizeVariants(query, subject, mode, ...)

### Arguments

`query` | A TxDb or `GRangesList` object that serves as the annotation. GFF files can be converted to TxDb objects with `makeTxDbFromGFF()` in the `GenomicFeatures` package.
`subject` | A VCF object containing the variants.
`mode` | `mode` can be a `VariantType` class or the name of a function. When `mode` is a `VariantType` class, counting is done with `locateVariants` and counts are summarized transcript-by-sample. Supported `VariantType` classes include `CodingVariants`, `IntronVariants`, `FiveUTRVariants`, `ThreeUTRVariants`, `SpliceSiteVariants` or `PromoterVariants`. `AllVariants()` and `IntergenicVariants` are not supported. See ?`locateVariants` for more detail on the variant classes. `mode` can also be the name of any counting function that outputs a `Hits` object. Variants will be summarized by the length of the `GRangesList` annotation (i.e., 'length-of-GRangesList'-by-sample).
`...` | Additional arguments passed to methods such as ignore.strand A `logical` indicating if strand should be igored when performing overlaps.

### Details

`summarizeVariants` uses the genotype information in a VCF file to determine which samples are positive for each variant. Variants are overlapped with the annotation and the counts are summarized annotation-by-sample. If the annotation is a `GRangesList` of transcripts, the count matrix will be transcripts-by-sample. If the `GRangesList` is genes, the count matrix will be gene-by-sample.

- Counting with locateVariants() :

  Variant counts are always summarized transcript-by-sample. When `query` is a `GRangesList`, it must be compatible with the `VariantType`-class given as the `mode` argument. The list below specifies the appropriate `GRangesList` for each `mode`.

  CodingVariants :

    coding (CDS) by transcript

  IntronVariants :

    introns by transcript

  FiveUTRVariants :

    five prime UTR by transcript

  ThreeUTRVariants :

    three prime UTR by transcript

  SpliceSiteVariants :

    introns by transcript

  PromoterVariants :

    list of transcripts

  When `query` is a `TxDb`, the appropriate region-by-transcript `GRangesList` listed above is extracted internally and used as the annotation.

- Counting with a user-supplied function :

  `subject` must be a `GRangesList` and `mode` must be the name of a function. The count function must take 'query' and 'subject' arguments and return a `Hits` object. Counts are summarized by the outer list elements of the `GRangesList`.

### Value

A `RangedSummarizedExperiment` object with count summaries in the `assays` slot. The `rowRanges` contains the annotation used for counting. Information in `colData` and `metadata` are taken from the VCF file.

### Author(s)

Valerie Obenchain

### See Also

`readVcf`, `predictCoding`, `locateVariants`

### Examples

      library(TxDb.Hsapiens.UCSC.hg19.knownGene)
      txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene

      ## Read variants from VCF.
      fl <- system.file("extdata", "chr22.vcf.gz", package="VariantAnnotation")
      vcf <- readVcf(fl, "hg19")
      ## Rename seqlevels to match TxDb; confirm the match.
      seqlevels(vcf) <- paste0("chr", seqlevels(vcf))
      intersect(seqlevels(vcf), seqlevels(txdb))

      ## ----------------------------------------
      ## Counting with locateVariants()
      ## ----------------------------------------
      ## TxDb as the 'query'
      coding1 <- summarizeVariants(txdb, vcf, CodingVariants())
      colSums(assays(coding1)$counts)

      ## GRangesList as the 'query'
      cdsbytx <- cdsBy(txdb, "tx")
      coding2 <- summarizeVariants(cdsbytx, vcf, CodingVariants())

      stopifnot(identical(assays(coding1)$counts, assays(coding2)$counts))

      ## Promoter region variants summarized by transcript
      tx <- transcripts(txdb)
      txlst <- splitAsList(tx, seq_len(length(tx)))
      promoter <- summarizeVariants(txlst, vcf,
                                    PromoterVariants(upstream=100, downstream=10))
      colSums(assays(promoter)$counts)

      ## ----------------------------------------
      ## Counting with findOverlaps()
      ## ----------------------------------------

      ## Summarize all variants by transcript
      allvariants <- summarizeVariants(txlst, vcf, findOverlaps)
      colSums(assays(allvariants)$counts)

[Package VariantAnnotation version 1.36.0 Index]