R/AllGenerics.R, R/Ps.R
Ps.RdP(s) will be approximated if no pairs are provided, or the exact P(s)
will be computed if a .pairs file is added to the HiCExperiment object
using pairsFile(x) <- "...".
distanceLaw(x, coords, ...)
# S4 method for class 'GInteractions,missing'
distanceLaw(x, by_chr = FALSE)
# S4 method for class 'HiCExperiment,missing'
distanceLaw(
x,
by_chr = FALSE,
filtered_chr = c("XII", "chrXII", "chr12", "12", "Mito", "MT", "chrM")
)
# S4 method for class 'PairsFile,missing'
distanceLaw(
x,
by_chr = FALSE,
filtered_chr = c("XII", "chrXII", "chr12", "12", "Mito", "MT", "chrM"),
chunk_size = 1e+05
)
# S4 method for class 'HiCExperiment,GRanges'
distanceLaw(x, coords, chunk_size = 1e+05)
# S4 method for class 'PairsFile,GRanges'
distanceLaw(x, coords, chunk_size = 1e+05)
localDistanceLaw(x, coords = coords)A HiCExperiment object
GRanges to specify which genomic loci to use when computing P(s)
Arguments passed to corresponding method
by_chr
filtered_chr
For pairs files which do not fit in memory, pick a number of pairs to parse by chunks (1e7 should be a good compromise)
a tibble
contacts_yeast <- contacts_yeast()
#> see ?HiContactsData and browseVignettes('HiContactsData') for documentation
#> loading from cache
ps <- distanceLaw(contacts_yeast)
#> pairsFile not specified. The P(s) curve will be an approximation.
ps
#> # A tibble: 35 × 5
#> binned_distance p norm_p norm_p_unity slope
#> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 0.731 0.731 1470429. 0
#> 2 15159 0.114 0.0000750 151. -1.35
#> 3 29540 0.0525 0.0000178 35.8 -1.92
#> 4 47574 0.0272 0.00000572 11.5 -2.36
#> 5 63322 0.0157 0.00000248 4.99 -2.76
#> 6 76619 0.0100 0.00000131 2.63 -3.01
#> 7 92709 0.00690 0.000000745 1.50 -3.12
#> 8 101980 0.00507 0.000000497 1 -3.16
#> 9 123396 0.00399 0.000000323 0.651 -3.12
#> 10 135735 0.00323 0.000000238 0.478 -2.87
#> # ℹ 25 more rows
local_ps <- localDistanceLaw(
contacts_yeast,
GenomicRanges::GRanges(
c("telomere" = "II:1-20000", "arm" = "II:300001-700000")
)
)
#> pairsFile not specified. The P(s) curve will be an approximation.
local_ps
#> # A tibble: 54 × 6
#> coords binned_distance p norm_p norm_p_unity slope
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 arm 1 0.680 0.680 926716. 0
#> 2 telomere 1 0.636 0.636 1190885. 0
#> 3 arm 15159 0.121 0.0000796 109. -1.12
#> 4 telomere 15159 0.129 0.0000854 160. -1.08
#> 5 arm 29540 0.0609 0.0000206 28.1 -1.80
#> 6 telomere 29540 0.0734 0.0000249 46.6 -1.73
#> 7 arm 47574 0.0321 0.00000675 9.21 -2.29
#> 8 telomere 47574 0.0342 0.00000720 13.5 -2.29
#> 9 arm 63322 0.0194 0.00000306 4.17 -2.72
#> 10 telomere 63322 0.0208 0.00000328 6.15 -2.92
#> # ℹ 44 more rows