Package 'tidyCoverage'

aggregate

Description

Bin coverage contained in a CoverageExperiment into an AggregatedCoverage object.

Usage

## S4 method for signature 'CoverageExperiment'
aggregate(x, bin = 1, ...)

Arguments

x	a CoverageExperiment object
bin	an integer to bin each assay by. The width of the AggregatedCoverage object should be a multiple of bin.
...	ignored

Value

an AggregatedCoverage object

Examples

data(ce)
aggregate(ce, bin = 10)

---

as_tibble

Description

Coerce an CoverageExperiment or AggregatedCoverage object into a tibble

Usage

## S3 method for class 'AggregatedCoverage'
as_tibble(x, ...)

Arguments

x	A data frame, list, matrix, or other object that could reasonably be coerced to a tibble.
...	Unused, for extensibility.

Value

tibble

Row names

The default behavior is to silently remove row names.

New code should explicitly convert row names to a new column using the rownames argument.

For existing code that relies on the retention of row names, call pkgconfig::set_config("tibble::rownames" = NA) in your script or in your package's .onLoad() function.

Life cycle

Using as_tibble() for vectors is superseded as of version 3.0.0, prefer the more expressive as_tibble_row() and as_tibble_col() variants for new code.

See Also

tibble() constructs a tibble from individual columns. enframe() converts a named vector to a tibble with a column of names and column of values. Name repair is implemented using vctrs::vec_as_names().

Examples

data(ac)
as_tibble(ac)

---

CoverageExperiment

Description

CoverageExperiment objects store coverages for individual tracks over different sets of features. The coverage assay contains a separate matrix for each combination of track x features. CoverageExperiment objects are instantiated using the CoverageExperiment() function, and can be coarsened using the coarsen() function.

Usage

CoverageExperiment(tracks, features, ...)

coarsen(x, window, ...)

## S4 method for signature 'BigWigFileList,GRangesList'
CoverageExperiment(
  tracks,
  features,
  width = NULL,
  center = FALSE,
  scale = FALSE,
  ignore.strand = TRUE,
  window = 1,
  BPPARAM = BiocParallel::bpparam()
)

## S4 method for signature 'BigWigFileList,GRanges'
CoverageExperiment(tracks, features, ...)

## S4 method for signature 'BigWigFileList,list'
CoverageExperiment(tracks, features, ...)

## S4 method for signature 'BigWigFile,GRangesList'
CoverageExperiment(tracks, features, ...)

## S4 method for signature 'BigWigFile,GRanges'
CoverageExperiment(tracks, features, ...)

## S4 method for signature 'BigWigFile,list'
CoverageExperiment(tracks, features, ...)

## S4 method for signature 'list,GRangesList'
CoverageExperiment(
  tracks,
  features,
  width = NULL,
  center = FALSE,
  scale = FALSE,
  ignore.strand = TRUE,
  window = 1,
  BPPARAM = BiocParallel::bpparam()
)

## S4 method for signature 'list,GRanges'
CoverageExperiment(tracks, features, ...)

## S4 method for signature 'list,list'
CoverageExperiment(tracks, features, ...)

## S4 method for signature 'RleList,GRangesList'
CoverageExperiment(tracks, features, ...)

## S4 method for signature 'RleList,GRanges'
CoverageExperiment(tracks, features, ...)

## S4 method for signature 'RleList,list'
CoverageExperiment(tracks, features, ...)

## S4 method for signature 'CoverageExperiment'
coarsen(x, window = 1, BPPARAM = BiocParallel::bpparam())

Arguments

tracks	A genomic track imported as a RleList or a named list of genomic tracks.
features	A set of features imported as GRanges or a named GRangesList.
...	Passed to the relevant method
x	a CoverageExperiment object
window	an integer to coarsen coverage by.
width	Width to resize each set of genomic features
scale, center	Logical, whether to scale and/or center tracks prior to summarization
ignore.strand	Logical, whether to not take the features strand information
BPPARAM	Passed to BiocParallel.

Value

A CoverageExperiment object

Examples

library(rtracklayer)
library(purrr)
library(plyranges)
TSSs_bed <- system.file("extdata", "TSSs.bed", package = "tidyCoverage")
features <- import(TSSs_bed) |> filter(strand == '+')

#############################################################################
## 1. Creating a `CoverageExperiment` object from a single BigWigFile
#############################################################################

RNA_fwd <- system.file("extdata", "RNA.fwd.bw", package = "tidyCoverage")
tracks <- BigWigFile(RNA_fwd)
CoverageExperiment(tracks, features, width = 5000)

#############################################################################
## 2. Creating a `CoverageExperiment` object from a BigWigFileList
#############################################################################

RNA_rev <- system.file("extdata", "RNA.rev.bw", package = "tidyCoverage")
tracks <- BigWigFileList(list(RNA_fwd = RNA_fwd, RNA_rev = RNA_rev))
CoverageExperiment(tracks, features, width = 5000)

#############################################################################
## 3. Creating a `CoverageExperiment` object from imported bigwig files
#############################################################################

tracks <- list(
    RNA_fwd = system.file("extdata", "RNA.fwd.bw", package = "tidyCoverage"),
    RNA_rev = system.file("extdata", "RNA.rev.bw", package = "tidyCoverage")
) |> map(import, as = 'Rle')
CoverageExperiment(tracks, features, width = 5000)

#############################################################################
## 4. Correct for strandness when recovering coverage
#############################################################################

TSSs_bed <- system.file("extdata", "TSSs.bed", package = "tidyCoverage")
features <- list(
    TSS_fwd = import(TSSs_bed) |> filter(strand == '+'), 
    TSS_rev = import(TSSs_bed) |> filter(strand == '-')
)
tracks <- list(
    RNA_fwd = system.file("extdata", "RNA.fwd.bw", package = "tidyCoverage"),
    RNA_rev = system.file("extdata", "RNA.rev.bw", package = "tidyCoverage")
) |> map(import, as = 'Rle')
CoverageExperiment(tracks, features, width = 5000, ignore.strand = FALSE)

#############################################################################
## Aggregating a `CoverageExperiment` object
#############################################################################
data(ce)
coarsen(ce, window = 10)

---

Example CoverageExperiment and AggregatedCoverage objects

Description

Two example objects are provided in the tidyCoverage package:

• ce: a CoverageExperiment dataset containing stranded RNA-seq coverage (forward and reverse) over Scc1 peaks (± 1kb).

• ac: an AggregatedCoverage object obtained with aggregate(ce).

Usage

data(ce)

data(ac)

Format

CoverageExperiment object containing 1 features set and 2 tracks.

AggregatedCoverage object containing 1 features set and 2 tracks.

Details

Data was generated in yeast (S288c) and aligned to reference R64-1-1.

---

Expand a CoverageExperiment object

Description

A CoverageExperiment object can be coerced into a tibble using the tidySummarizedExperiment package, but this will not turn each coverage matrix into a "long" format. The expand function provided here allows one to coerce a CoverageExperiment object into a long data frame, and adds the ranges and seqnames to the resulting tibble.

Usage

## S3 method for class 'CoverageExperiment'
expand(data, ..., .name_repair = NULL)

Arguments

data	A data frame.
...	<data-masking> Specification of columns to expand or complete. Columns can be atomic vectors or lists. To find all unique combinations of x, y and z, including those not present in the data, supply each variable as a separate argument: expand(df, x, y, z) or complete(df, x, y, z). To find only the combinations that occur in the data, use nesting: expand(df, nesting(x, y, z)). You can combine the two forms. For example, expand(df, nesting(school_id, student_id), date) would produce a row for each present school-student combination for all possible dates. When used with factors, expand() and complete() use the full set of levels, not just those that appear in the data. If you want to use only the values seen in the data, use forcats::fct_drop(). When used with continuous variables, you may need to fill in values that do not appear in the data: to do so use expressions like year = 2010:2020 or year = full_seq(year,1).
.name_repair	One of "check_unique", "unique", "universal", "minimal", "unique_quiet", or "universal_quiet". See vec_as_names() for the meaning of these options.

Value

a tibble object

Grouped data frames

With grouped data frames created by dplyr::group_by(), expand() operates within each group. Because of this, you cannot expand on a grouping column.

See Also

complete() to expand list objects. expand_grid() to input vectors rather than a data frame.

Examples

data(ce)
ce
expand(ce)

---

Plotting functions

Description

Plotting functions for tidyCoverage objects. Two geoms are provided:

• geom_coverage(): for plotting coverages over individual loci.

• geom_aggrcoverage(): for plotting aggregated coverages with confidence intervals.

See the Details section for more information on the aesthetics used by each geom.

Usage

geom_aggrcoverage(
  mapping = NULL,
  data = NULL,
  ...,
  unit = c("kb", "Mb", "b"),
  ci = TRUE,
  grid = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_coverage(
  mapping = NULL,
  data = NULL,
  ...,
  type = c("area", "line"),
  unit = c("kb", "Mb", "b"),
  grid = FALSE,
  alpha = 0.6,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  raster = TRUE
)

scale_y_coverage()

scale_x_genome(unit = c("kb", "Mb", "b"))

Arguments

mapping	Set of aesthetic mappings created by aes(). By default, no color/fill aesthetic is specified, but they can be assigned to a variable with mapping = aes(...). Note that x and y are automatically filled.
data	Data frame passed to geom_*. Typically a CoverageExperiment object (expanded to a tibble) or a AggregatedCoverage object.
..., na.rm, show.legend, inherit.aes	Argument passed to ggplot internal functions
unit	Rounding of x axis (any of c('b', 'kb', 'Mb')).
ci	Should the confidence interval be plotted by geom_aggrcoverage()? (default: TRUE)
grid	Should the plot grid by displayed? (default: FALSE).
type	Choose between "line" and "area" style for geom_coverage().
alpha	Transparency level for geom_coverage() (default: 0.6).
raster	Should the plot be rasterized for faster rendering? (default: TRUE)

Details

These geoms are drawn using geom_line/ribbon/area() so they support the same aesthetics: colour, linetype and linewidth. Both geoms also support the unit argument to control the x axis units (b, kb, Mb).

In addition, they each support additional arguments:

• geom_coverage uses a type argument to switch between line plot and area plots;

• geom_aggrcoverage uses a ci argument to toggle the confidence interval display.

Value

A ggplot object

Examples

library(rtracklayer)
library(plyranges)
library(ggplot2)
library(purrr)
TSSs_bed <- system.file("extdata", "TSSs.bed", package = "tidyCoverage")
features <- list(
    TSS_fwd = import(TSSs_bed) |> filter(strand == '+'), 
    TSS_rev = import(TSSs_bed) |> filter(strand == '-'), 
    conv_sites = import(system.file("extdata", "conv_transcription_loci.bed", package = "tidyCoverage"))
)
tracks <- list(
    RNA_fwd = system.file("extdata", "RNA.fwd.bw", package = "tidyCoverage"),
    RNA_rev = system.file("extdata", "RNA.rev.bw", package = "tidyCoverage"), 
    Scc1 = system.file("extdata", "Scc1.bw", package = "tidyCoverage")
) |> map(import, as = 'Rle')
ce <- CoverageExperiment(tracks, features, width = 5000, center = TRUE, scale = TRUE)
ac <- aggregate(ce) 

#############################################################################
## 1. Plotting aggregated coverage
#############################################################################

ac |> 
    as_tibble() |> 
    ggplot() + 
    geom_aggrcoverage(aes(col = track)) + 
    facet_grid(track ~ features) + 
    geom_vline(xintercept = 0, color = 'black', linetype = 'dashed', linewidth = 0.5)

#############################################################################
## 2. Plotting track coverages over individual loci
#############################################################################

ce2 <- CoverageExperiment(
    tracks, 
    GRangesList(list(locus1 = "II:400001-455000", locus2 = "IV:720001-775000")), 
    window = 50
)
expand(ce2) |> 
    mutate(coverage = ifelse(track != 'Scc1', scales::oob_squish(coverage, c(0, 50)), coverage)) |>
    ggplot() + 
    geom_coverage(aes(fill = track)) + 
    facet_grid(track~features, scales = 'free')

---

show method for CoverageExperiment and AggregatedCoverage objects

Description

show method for CoverageExperiment and AggregatedCoverage objects

Arguments

object	a CoverageExperiment or AggregatedCoverage object
setup	a setup object returned from pillar::tbl_format_setup().

Value

⁠Prints a message to the console describing the contents of the ⁠CoverageExperimentorAggregatedCoverage' objects.

Examples

data(ce)
print(ce)
data(ac)
print(ac)

---