BigWigFile-class {rtracklayer} | R Documentation

## BigWig Import and Export

### Description

These functions support the import and export of the UCSC BigWig format, a compressed, binary form of WIG/BEDGraph with a spatial index and precomputed summaries. These functions do not work on Windows.

### Usage

    ## S4 method for signature 'BigWigFile,ANY,ANY'
    import(con, format, text,
                       selection = BigWigSelection(which, ...),
                       which = con,
                       as = c("GRanges", "RleList", "NumericList"), ...)
    import.bw(con, ...)

    ## S4 method for signature 'ANY,BigWigFile,ANY'
    export(object, con, format, ...)
    ## S4 method for signature 'GenomicRanges,BigWigFile,ANY'
    export(object, con, format,
                       dataFormat = c("auto", "variableStep", "fixedStep",
                         "bedGraph"), compress = TRUE, fixedSummaries = FALSE)
    export.bw(object, con, ...)

### Arguments

`con` | A path, URL or `BigWigFile` object. Connections are not supported. For the functions ending in `.bw`, the file format is indicated by the function name. For the `export` and `import` methods, the format must be indicated another way. If `con` is a path, or URL, either the file extension or the `format` argument needs to be “bigWig” or “bw”.
`object` | The object to export, should be an `RleList`, `IntegerList`, `NumericList`, `GRanges` or something coercible to a `GRanges`.
`format` | If not missing, should be “bigWig” or “bw” (case insensitive).
`text` | Not supported.
`as` | Specifies the class of the return object. Default is `GRanges`, which has one range per range in the file, and a score column holding the value for each range. For `NumericList`, one numeric vector is returned for each range in the `selection` argument. For `RleList`, there is one `Rle` per sequence, and that `Rle` spans the entire sequence.
`selection` | A `BigWigSelection` object indicating the ranges to load.
`which` | A range data structure coercible to `IntegerRangesList`, like a `GRanges`, or a `BigWigFile`. Only the intervals in the file overlapping the given ranges are returned. By default, the value is the `BigWigFile` itself. Its `Seqinfo` object is extracted and coerced to a `IntegerRangesList` that represents the entirety of the file.
`dataFormat` | Probably best left to “auto”. Exists only for historical reasons.
`compress` | If `TRUE`, compress the data. No reason to change this.
`fixedSummaries` | If `TRUE`, compute summaries at fixed resolutions corresponding to the default zoom levels in the Ensembl genome browser (with some extrapolation): 30X, 65X, 130X, 260X, 450X, 648X, 950X, 1296X, 4800X, 19200X. Otherwise, the resolutions are dynamically determined by an algorithm that computes an initial summary size by initializing to 10X the size of the smallest feature and doubling the size as needed until the size of the summary is less than half that of the data (or there are no further gains). It then computes up to 10 more levels of summary, quadrupling the size each time, until the summaries start to exceed the sequence size.
`...` | Arguments to pass down to methods to other methods. For import, the flow eventually reaches the `BigWigFile` method on `import`.

### Value

A `GRanges` (default), `RleList` or `NumericList`. `GRanges` return ranges with non-zero score values in a `score` metadata column. The length of the `NumericList` is the same length as the `selection` argument (one list element per range). The return order in the `NumericList` matches the order of the `BigWigSelection` object.

### `BigWigFile` objects

A `BigWigFile` object, an extension of `RTLFile` is a reference to a BigWig file. To cast a path, URL or connection to a `BigWigFile`, pass it to the `BigWigFile` constructor.

BigWig files are more complex than most track files, and there are a number of methods on `BigWigFile` for accessing the additional information:

  `seqinfo(x)`: Gets the `Seqinfo` object indicating the lengths of the sequences for the intervals in the file. No circularity or genome information is available.

  `summary(ranges = as(seqinfo(object), "GenomicRanges"), size = 1L, type = c("mean", "min", "max", "coverage", "sd"), defaultValue = NA_real_), as = c("GRangesList", "RleList", "matrix"), ...`: Aggregates the intervals in the file that fall into `ranges`, which should be something coercible to `GRanges`. The aggregation essentially compresses each sequence to a length of `size`. The algorithm is specified by `type`; available algorithms include the mean, min, max, coverage (percent sequence covered by at least one feature), and standard deviation. When a window contains no features, `defaultValue` is assumed. The result type depends on `as`, and can be a GRangesList, RleList or matrix, where the number elements (or rows) is equal to the length of `ranges`. For `as="matrix"`, there must be one unique value of `size`, which is equal to the number of columns in the result. The `as="matrix"` case is the only one that supports a `size` greater than the width of the corresponding element in `ranges`, where values are interpolated to yield the matrix result. The driving use case for this is visualization of coverage when the screen space is small compared to the viewed portion of the sequence. The operation is very fast, as it leverages cached multi-level summaries present in every BigWig file.

  If a summary statistic is not available / cannot be computed for a given range a warning is thrown and the defaultValue `NA_real_` is returned.

When accessing remote data, the UCSC library caches data in the ‘/tmp/udcCache’ directory. To clean the cache, call `cleanBigWigCache(maxDays)`, where any files older than `maxDays` days old will be deleted.

### `BigWigFileList` objects

A `BigWigFileList()` provides a convenient way of managing a list of `BigWigFile` instances.

### Author(s)

Michael Lawrence

### See Also

`wigToBigWig` for converting a WIG file to BigWig.

### Examples

    if (.Platform$OS.type != "windows") {
      test_path <- system.file("tests", package = "rtracklayer")
      test_bw <- file.path(test_path, "test.bw")

      ## GRanges
      ## Returns ranges with non-zero scores.
      gr <- import(test_bw)
      gr

      which <- GRanges(c("chr2", "chr2"), IRanges(c(1, 300), c(400, 1000)))
      import(test_bw, which = which)

      ## RleList
      ## Scores returned as an RleList is equivalent to the coverage.
      ## Best option when 'which' or 'selection' contain many small ranges.
      mini <- narrow(unlist(tile(which, 50)), 2)
      rle <- import(test_bw, which = mini, as = "RleList")
      rle

      ## NumericList
      ## The 'which' is stored as metadata:
      track <- import(test_bw, which = which, as = "NumericList")
      metadata(track)

    ## Not run:
      test_bw_out <- file.path(tempdir(), "test_out.bw")
      export(test, test_bw_out)

    ## End(Not run)

      bwf <- BigWigFile(test_bw)
      track <- import(bwf)

      seqinfo(bwf)

      summary(bwf) # for each sequence, average all values into one
      summary(bwf, range(head(track))) # just average the first few features
      summary(bwf, size = seqlengths(bwf) / 10) # 10X reduction
      summary(bwf, type = "min") # min instead of mean
      summary(bwf, track, size = 10, as = "matrix") # each feature 10 windows
    }

[Package rtracklayer version 1.48.0 Index]