Extract data for one or more anchor regions

Extract assay values for each read (or sample) and each position in a set of anchor regions of the same width. The anchor regions are defined by their genomic midpoint coordinate and the width.

Usage

getAnchorRegions(
  se,
  assayName = "mod_prob",
  regionMidpoints,
  regionWidth,
  prune = TRUE,
  ignore.strand = FALSE,
  reverseMinusStrandRegions = FALSE,
  verbose = FALSE
)

Arguments

se

A SummarizedExperiment object.

assayName

Character vector, the assay(s) from which to extract values.

regionMidpoints

Either a GPos object or a character vector that can be coerced into a GPos object, representing the midpoints of the desired anchor regions.

regionWidth

Integer scalar, the desired width of the anchor regions. Must be an odd value.

prune

Logical scalar. If TRUE (the default), samples for which there are no reads overlapping any of the anchor regions in any of the read-level assays in assayName will be completely removed from the returned SummarizedExperiment (also from colData). If FALSE, such samples are retained (in assays with read-level data as a zero-column NAMatrix, in other assays as a dense matrix with a single column of NA values).

ignore.strand

Logical scalar, whether to ignore the strand information when matching anchor regions with observations. Will be passed on to GenomicRanges::match(). If TRUE, a pruning step will be applied to ensure that each genomic position is represented by at most one row in the object. If multiple rows are found corresponding to the same position (on different strands), the one with the highest number of supporting reads (determined by the Nvalid, Nmod, or mod_prob assay, in this preference order, depending on what is present in se) will be retained.

reverseMinusStrandRegions

Logical scalar. If TRUE, data extracted from regions on the negative strand will be reversed before they are concatenated with the rest of the data, so that negative relative positions correspond to regions upstream of the region midpoint.

verbose

Logical scalar. If TRUE, report on progress.

Value

A SummarizedExperiment with rows representing relative positions within an anchor region (the midpoint of the region corresponds to a relative position of 0) and columns representing samples. Each column of the assay is an NaArray (if assayName is a read-level assay) or a dense matrix (otherwise), with columns representing read-anchor region (or sample-anchor region) combinations. The region column of the colData records which anchor region a given column corresponds to.

Author

Charlotte Soneson

Examples

library(SummarizedExperiment)
modbamfiles <- system.file("extdata", c("6mA_1_10reads.bam", "6mA_2_10reads.bam"),
                           package = "footprintR")
se <- readModBam(bamfiles = modbamfiles, regions = "chr1:6920000-6940000",
                 modbase = "a", verbose = FALSE)
se <- flattenReadLevelAssay(se)
ar <- getAnchorRegions(se, assayName = c("mod_prob", "FracMod", "Nvalid"),
                       regionMidpoints = c("chr1:6929389:-", "chr1:6935630:-"),
                       regionWidth = 9)

## Modification probabilities
assay(ar)
#> DataFrame with 9 rows and 2 columns
#>                                        s1
#>                                <NaMatrix>
#> 1                            NA:NA:NA:...
#> 2                              0:NA:0:...
#> 3                              0:NA:0:...
#> 4 0.955078125:0.068359375:0.654296875:...
#> 5 0.455078125:0.111328125:0.994140625:...
#> 6                            NA:NA:NA:...
#> 7                            NA:NA:NA:...
#> 8                    NA:0:0.068359375:...
#> 9                            NA:NA:NA:...
#>                                        s2
#>                                <NaMatrix>
#> 1                            NA:NA:NA:...
#> 2          0.990234375:0.103515625:NA:...
#> 3 0.994140625:0.064453125:0.939453125:...
#> 4          0.990234375:0.056640625:NA:...
#> 5                   0.970703125:NA:NA:...
#> 6                            NA:NA:NA:...
#> 7                   0.955078125:NA:NA:...
#> 8          NA:0.166015625:0.423828125:...
#> 9                            NA:NA:NA:...

## Region assignment
colData(ar)
#> DataFrame with 2 rows and 4 columns
#>         sample
#>    <character>
#> s1          s1
#> s2          s2
#>                                                                                                                              region_mod_prob
#>                                                                                                                                       <List>
#> s1 chr1:6929385-6929393..:chr1:6929385-6929393:-,chr1:6929385-6929393..:chr1:6929385-6929393:-,chr1:6929385-6929393..:chr1:6929385-6929393:-
#> s2 chr1:6929385-6929393..:chr1:6929385-6929393:-,chr1:6929385-6929393..:chr1:6929385-6929393:-,chr1:6929385-6929393..:chr1:6929385-6929393:-
#>                                                                                 region_FracMod
#>                                                                                         <List>
#> s1 chr1:6929385-6929393..:chr1:6929385-6929393:-,chr1:6935626-6935634..:chr1:6935626-6935634:-
#> s2 chr1:6929385-6929393..:chr1:6929385-6929393:-,chr1:6935626-6935634..:chr1:6935626-6935634:-
#>                                                                                  region_Nvalid
#>                                                                                         <List>
#> s1 chr1:6929385-6929393..:chr1:6929385-6929393:-,chr1:6935626-6935634..:chr1:6935626-6935634:-
#> s2 chr1:6929385-6929393..:chr1:6929385-6929393:-,chr1:6935626-6935634..:chr1:6935626-6935634:-