Bins putative interactions by distance

Places putative interactions into equally-sized bins based on the distances they span.

bin_interactions(
  interactions,
  fragments,
  bins = 5,
  min_dist = 2500,
  max_dist = Inf,
  log_file = NA
)

Arguments

interactions	Data table containing putative interactions. Columns called baitID, preyID, N, storing the bait fragment ID, prey fragment ID and readcount, respectively.
fragments	Data table containing fragment information. Columns called chrom, chromStart, chromEnd, ID, storing the chromosome, starting coordinate, ending coordinate and ID of a fragment, respectively.
bins	Number of bins to place the interactions into.
min_dist	Minimum distance interactions must span to be included in the analysis. Distance is defined between fragment midpoints.
max_dist	Maximum distance interactions can span to be included in the analysis. Distance is defined between fragment midpoints.
log_file	Path to a log file.

Value

List containing the binned interactions ($interactions) and an overview of bins ($bins).

Examples

base = system.file("extdata",package="peaky")

interactions_file = paste0(base,"/counts.tsv")
fragments_file = paste0(base,"/fragments.bed")

interactions = data.table::fread(interactions_file)
fragments = data.table::fread(fragments_file)

if (FALSE) BI = bin_interactions(interactions, fragments, bins=5)
print(BI)
#> function (mu.link = "logit") 
#> {
#>     mstats <- checklink("mu.link", "Binomial", substitute(mu.link), 
#>         c("logit", "probit", "cloglog", "cauchit", "log", "own"))
#>     structure(list(family = c("BI", "Binomial"), parameters = list(mu = TRUE), 
#>         nopar = 1, type = "Discrete", mu.link = as.character(substitute(mu.link)), 
#>         mu.linkfun = mstats$linkfun, mu.linkinv = mstats$linkinv, 
#>         mu.dr = mstats$mu.eta, dldm = function(y, mu, bd) (y - 
#>             bd * mu)/(mu * (1 - mu)), d2ldm2 = function(mu, bd) -(bd/(mu * 
#>             (1 - mu))), G.dev.incr = function(y, mu, bd, ...) -2 * 
#>             dBI(y, bd, mu, log = TRUE), rqres = expression(rqres(pfun = "pBI", 
#>             type = "Discrete", ymin = 0, y = y, mu = mu, bd = bd)), 
#>         mu.initial = expression({
#>             mu <- (y + 0.5)/(bd + 1)
#>         }), mu.valid = function(mu) all(mu > 0) && all(mu < 1), 
#>         y.valid = function(y) all(y >= 0), mean = function(bd, 
#>             mu) bd * mu, variance = function(bd, mu) bd * mu * 
#>             (1 - mu)), class = c("gamlss.family", "family"))
#> }
#> <bytecode: 0x562087890c48>
#> <environment: namespace:gamlss.dist>