Pileup Hi-C pixels

pileupPixels optionally removes short interactions that intersect the diagonal before extracting then aggregating square regions around each pixel from Hi-C files. This is also known as aggregate peak analysis (APA)

Usage

pileupPixels(
  x,
  files,
  binSize,
  buffer = 5,
  removeShort = TRUE,
  minPairDist = 0,
  normalize = TRUE,
  FUN = sum,
  nBlocks = 5,
  verbose = TRUE,
  BPPARAM = bpparam(),
  ...
)

# S4 method for GInteractions,character,numeric
pileupPixels(
  x,
  files,
  binSize,
  buffer = 5,
  removeShort = TRUE,
  minPairDist = 0,
  normalize = TRUE,
  FUN = sum,
  nBlocks = 5,
  verbose = TRUE,
  BPPARAM = bpparam(),
  ...
)

Arguments

x

GInteractions object containing interactions to extract from Hi-C files. These should be pixels of a single `binSize` in width.

files

Character file paths to `.hic` files.

binSize

Integer (numeric) describing the resolution (range widths) of the paired data.

buffer

Integer indicating the buffer size, or number of pixels

removeShort

Boolean, whether to remove short pairs (Default) or not.

minPairDist

Pairs with a distance less than or equal to this value will be filtered out.

normalize

Boolean, whether to normalize the aggregated values to the number of interactions (after filtering out short pairs - if applicable).

FUN

Function to use for aggregating.

nBlocks

Number of blocks for block-processing arrays. Default is 5. Increase this for large datasets. To read and process all data at once, set this value to 1.

verbose

Boolean (TRUE or FALSE) describing whether to report block-processing progress.

BPPARAM

Parallelization params (passed to `BiocParallel::bplapply()`). Default is the result of `BiocParallel::bpparams()`. Parallel processing is not available when `by=interactions`.

...

Additional arguments passed to `pullHicMatrices()`.

Value

A DelayedMatrix of aggregated counts.

Details

Note that pair distance filtering is done after expanding interactions to matrices.

Examples

## Load marinerData
if (!require("marinerData", quietly = TRUE))
    BiocManager::install("marinerData")

## Read .hic file paths
hicFile <- marinerData::LEUK_HEK_PJA30_inter_30.hic()
#> see ?marinerData and browseVignettes('marinerData') for documentation
#> loading from cache
names(hicFile) <- "WT"

## Loops
loops <-
    WT_5kbLoops.txt() |>
    setNames("WT") |>
    read.table(header=TRUE, nrows=1000) |>
    as_ginteractions(keep.extra.columns=FALSE) |>
    assignToBins(binSize=5e3)
#> see ?marinerData and browseVignettes('marinerData') for documentation
#> loading from cache

## Removes the "chr" prefix for compatibility
## with the preprocessed hic files
GenomeInfoDb::seqlevelsStyle(loops) <- 'ENSEMBL'

## APA
mat <- pileupPixels(
    x=loops,
    files=hicFile,
    binSize=5e3,
    minPairDist=50e3,
    normalize=FALSE
)