interpret_peaky: Interprets models fitted with peaky
In cqgd/pky: Capture Hi-C calling algorithm

Description Usage Arguments Value Details Examples

Extracts the marginal posterior probabilities of contact and other relevant statistics from the RJMCMC results and merges these with bait-associated information.

1	interpret_peaky(bait, peaks, omega_power, log_file = NA)

`bait`	Data table containing the putative interactions of a bait, having the columns 'baitID', 'dist', and 'residual'. These report the bait ID, its distance to putative preys, and the adjusted readcounts for its interactions with them, respectively.
`peaks`	The models fitted by peaky.
`omega_power`	The same value as used when running peaky, i.e. the expected decay of adjusted read counts around a truly interacting prey. See details.

A data table containing bait-associated information, posterior probabilities of contact and other statistics.

The steepness of the function to be fitted to putative peaks is determined by ω according to β \exp{- \abs{ω * d}}, where β represents peak height and d the distance from the center of the peak in bp.

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)
## Not run: 
BI = bin_interactions(interactions, fragments, bins=5)
models = by(BI$interactions, BI$interactions$dist.bin, model_bin, subsample_size=1000)
residuals = lapply(models, "[[", "residuals")
bins = split(BI$interactions, BI$interactions$dist.bin)

BTS = split_baits(bins, residuals)

relevant_bait = BTS[baitID==618421]
omega_power=4.7
PKS = peaky(relevant_bait, omega_power, iterations=1e6)

interpret_peaky(relevant_bait, PKS, omega_power)

## End(Not run)