chicane {chicane}

chicane

Description

Run full method for detecting significant interactions in capture Hi-C experiments, starting either from a BAM file or preprocessed data from prepare.data

Usage

chicane(
  bam = NULL,
  baits = NULL,
  fragments = NULL,
  interactions = NULL,
  replicate.merging.method = "sum",
  distribution = "negative-binomial",
  include.zeros = "none",
  bait.filters = c(0, 1),
  target.filters = c(0, 1),
  distance.bins = NULL,
  multiple.testing.correction = c("bait-level", "global"),
  adjustment.terms = NULL,
  remove.adjacent = FALSE,
  temp.directory = NULL,
  keep.files = FALSE,
  maxit = 100,
  epsilon = 1e-08,
  cores = 1,
  trace = FALSE,
  verbose = FALSE,
  interim.data.dir = NULL
)

Arguments

bam

Path to a BAM file

baits

Path to a BED file containing the baits

fragments

Path to a BED file containing all restriction fragments in the genome

interactions

Data table or path to a text file detailing fragment interactions, typically from prepare.data. Can be used instead of bam/baits/fragments specification if the text files have already been prepared.

replicate.merging.method

Method that should be used for merging replicates, if applicable

distribution

Name of distribution of the counts. Options are 'negative-binomial', 'poisson', 'truncated-poisson', and 'truncated-negative-binomial'

include.zeros

String specifying what zero counts to include. Options are none (default), cis, and all.

bait.filters

Vector of length two, where the first element corresponds to the lower-end filter and the second to the upper-end filter. When global multiple testing correction is performed, altering the bait filtering settings may affect the number of significant results.

target.filters

Vector of length two, giving lower and higher filter, respectively. Changing this filtering setting may affect multiple testing correction by altering the number of tests performed.

distance.bins

Number of bins to split distance into. Models are fit separately in each bin.

multiple.testing.correction

String specifying how multiple testing correction should be performed, by bait or globally.

adjustment.terms

Character vector of extra terms to adjust for in the model fit.

remove.adjacent

Logical indicating whether to remove all reads mapping to adjacent restriction fragments.

temp.directory

Directory where temporary files should be stored. Defaults to current directory.

keep.files

Logical indicating whether to keep temporary files

maxit

Maximum number of IWLS iterations for fitting the model (passed to glm.control)

epsilon

Positive convergence tolerance for Poisson and negative binomial models. Passed to glm.control

cores

Integer value specifying how many cores to use to fit model for cis-interactions.

trace

Logical indicating if output should be produced for each of model fitting procedure. Passed to glm.control or gamlss.control

verbose

Logical indicating whether to print progress reports.

interim.data.dir

Path to directory to store intermediate QC data and plots. NULL indicate skip intermediate results.

Value

Data table with columns

target.id

String in chrN:start-end format identifying target fragment

bait.id

String in chrN:start-end format identifying bait fragment

target.chr

Chromosome of target fragment

target.start

Start coordinate of target fragment (zero-based)

target.end

End coordinate of target fragment

bait.chr

Chromosome of bait fragment

bait.start

Start coordinate of bait fragment (zero-based)

bait.end

End coordinate of bait fragment

bait.to.bait

Boolean indicating if the interaction is bait-to-bait (i.e. the fragment listed as target is also a bait)

bait.trans.count

The number of reads linking the bait to fragments in trans (a measure of "interactibility")

target.trans.count

The number of reads linking the target to fragments in trans (a measure of "interactibility")

distance

Distance between the midpoints of the bait and target fragments (basepairs). NA for trans interactions

count

The number of reads linking the two fragments

expected

The expected number of reads linking the two fragments under the fitted model

p.value

P-value for test of the observed number of reads significantly exceeding the expected count

q.value

FDR-corrected p-value

Author(s)

Erle Holgersen <[e-mail]>

Examples

if( bedtools.installed() ) {
  # start from BAM file
  bam <- system.file('extdata', 'Bre80_2q35.bam', package = 'chicane');
  baits <- system.file('extdata', '2q35.bed', package = 'chicane');
  fragments <- system.file('extdata', 'GRCh38_HindIII_chr2.bed.gz', package = 'chicane');
  results <- chicane(
	bam = bam, 
	baits = baits, 
	fragments = fragments
	);
}

# start from pre-processed data
data(bre80); 
results <- chicane(interactions = bre80);