arithmetics: HiContacts arithmetics functionalities

In js2264/cooleR: Analysing cool files in R with HiContacts

HiContacts arithmetics functionalities

Description

Different arithmetic operations can be performed on Hi-C contact matrices:

• normalize a contact matrix using iterative correction;

• detrend a contact matrix, i.e. remove the distance-dependent contact trend;

• autocorrelate a contact matrix: this is is typically done to highlight large-scale compartments;

• divide one contact matrix by another;

• merge multiple contact matrices;

• despeckle (i.e. smooth out) a contact matrix out;

• aggregate (average) a contact matrices over a set of genomic loci of interest;

• boost Hi-C signal by enhancing long-range interactions while preserving short- range interactions (this is adapted from Boost-HiC);

• subsample interactions using a proportion or a fixed number of final interactions.

• coarsen a contact matrix to a larger (coarser) resolution

Usage

## S4 method for signature 'HiCExperiment'
aggregate(
  x,
  targets,
  flankingBins = 51,
  maxDistance = NULL,
  BPPARAM = BiocParallel::bpparam()
)

detrend(x, use.scores = "balanced")

autocorrelate(x, use.scores = "balanced", detrend = TRUE, ignore_ndiags = 3)

divide(x, by, use.scores = "balanced", pseudocount = 0)

## S4 method for signature 'HiCExperiment,HiCExperiment'
merge(x, y, ..., use.scores = "balanced", FUN = mean)

despeckle(x, use.scores = "balanced", focal.size = 1)

boost(x, use.scores = "balanced", alpha = 1, full.replace = FALSE)

coarsen(x, bin.size)

## S4 method for signature 'HiCExperiment'
normalize(
  object,
  use.scores = "count",
  niters = 200,
  min.nnz = 10,
  mad.max = 3
)

subsample(x, prop)

Arguments

x, y, object	a HiCExperiment object
targets	Set of chromosome coordinates for which interaction counts are extracted from the Hi-C contact file, provided as a GRanges object (for diagnoal-centered loci) or as a GInteractions object (for off-diagonal coordinates).
flankingBins	Number of bins on each flank of the bins containing input targets.
maxDistance	Maximum distance to use when compiling distance decay
BPPARAM	BiocParallel parameters
use.scores	Which scores to use to perform operations
detrend	Detrend matrix before performing autocorrelation
ignore_ndiags	ignore N diagonals when calculating correlations
by	a HiCExperiment object
pseudocount	Add a pseudocount when dividing matrices (Default: 0)
...	HiCExperiment objects. For aggregate, targets (a set of GRanges or GInteractions).
FUN	merging function
focal.size	Size of the smoothing rectangle
alpha	Power law scaling factor. As indicated in Boost-HiC documentation, the alpha parameter influences the weighting of contacts: if alpha < 1 long-range interactions are prioritized; if alpha >> 1 short-range interactions have more weight when computing the distance matrix.
full.replace	Whether to replace the entire set of contacts, rather than only filling the missing interactions (count=0) (Default: FALSE)
bin.size	Bin size to coarsen a HiCExperiment at
niters	Number of iterations for ICE matrix balancing
min.nnz	Filter bins with less than min.nnz non-zero elements when performing ICE matrix balancing
mad.max	Filter out bins whose log coverage is less than mad.max median absolute deviations below the median bin log coverage.
prop	Float between 0 and 1, or integer corresponding to the # of

Value

a HiCExperiment object with extra scores

Examples

#### -----
#### Normalize a contact matrix
#### -----

library(HiContacts)
contacts_yeast <- contacts_yeast()
normalize(contacts_yeast)

#### -----
#### Detrending a contact matrix
#### -----

detrend(contacts_yeast)

#### -----
#### Auto-correlate a contact matrix
#### -----

autocorrelate(contacts_yeast)

#### -----
#### Divide 2 contact matrices
#### -----

contacts_yeast <- refocus(contacts_yeast, 'II')
contacts_yeast_eco1 <- contacts_yeast_eco1() |> refocus('II')
divide(contacts_yeast_eco1, by = contacts_yeast)

#### -----
#### Merge 2 contact matrices
#### -----

merge(contacts_yeast_eco1, contacts_yeast)

#### -----
#### Despeckle (smoothen) a contact map
#### -----

despeckle(contacts_yeast)

#### -----
#### Aggregate a contact matrix over centromeres, at different scales
#### -----

contacts <- contacts_yeast() |> zoom(resolution = 1000)
centros <- topologicalFeatures(contacts, 'centromeres')
aggregate(contacts, targets = centros, flankingBins = 51)

#### -----
#### Enhance long-range interaction signal
#### -----

contacts <- contacts_yeast() |> zoom(resolution = 1000) |> refocus('II')
boost(contacts, alpha = 1)

#### -----
#### Subsample & "coarsen" contact matrix 
#### -----

subcontacts <- subsample(contacts, prop = 100000)
coarsened_subcontacts <- coarsen(subcontacts, bin.size = 4000)

js2264/cooleR documentation built on Oct. 3, 2024, 2:51 a.m.