Compute a scalogram of contacts

scalogram(x, dist_min = 0, nbins = 250, probs = c(0.25, 0.5, 0.75))

Arguments

x: A HiCExperiment object
dist_min: Minimum distance for interactions to be considered.
nbins: Number of bins to divide each chromosome
probs: Quantiles of interactions

Value

a tibble

Examples

contacts_yeast <- HiCExperiment::contacts_yeast()
#> see ?HiContactsData and browseVignettes('HiContactsData') for documentation
#> loading from cache
pairsFile(contacts_yeast) <- HiContactsData::HiContactsData(
  'yeast_wt', format = 'pairs.gz'
)
#> see ?HiContactsData and browseVignettes('HiContactsData') for documentation
#> loading from cache
scalo <- scalogram(contacts_yeast['II'])
#> Importing pairs file /github/home/.cache/R/ExperimentHub/1bea16b12b37_7753 in memory. This may take a while...
scalo
#> # A tibble: 750 × 4
#> # Groups:   chr, binned_pos [250]
#>    chr   binned_pos prob  dist_quantile
#>    <chr>      <dbl> <fct>         <dbl>
#>  1 II            1  0.25         11094.
#>  2 II            1  0.5          26303 
#>  3 II            1  0.75         59908.
#>  4 II         3254. 0.25          9491 
#>  5 II         3254. 0.5          23273 
#>  6 II         3254. 0.75         47260 
#>  7 II         6506. 0.25          3548.
#>  8 II         6506. 0.5          13478.
#>  9 II         6506. 0.75         39133 
#> 10 II         9759. 0.25          3110 
#> # ℹ 740 more rows