shaman_kk_norm: Compute a score matrix for observed data based on the...

In tanaylab/shaman: shaman - Sampling HiC contAct Matrices for Aparametric Normalization

Compute a score matrix for observed data based on the expected for a given set of points

Description

shaman_kk_norm

Usage

shaman_kk_norm(obs, exp, points, k = 100, k_exp = 100)

Arguments

obs	Dataframe containing the observed points
exp	Dataframe containing the expected (shuffled) points.
points	A score will be computed for each of the points.
k	The number of neighbor distances used for the score on observed data. For higher resolution maps, increase k. For lower resolution maps, decrease k.
k_exp	The number of neighbor distances used for the score on expected data. Should reflect the ratio between the total number of observed and expected over the entire chromosome.

Details

This function receives observed and expected data and compute the score on a given set of points. The score for a point is the KS D-statistic of the distances to the points k-nearest-neighbors

Value

NULL if insufficient observed data, otherwise resturns a list containing 3 elements: 1) points - start1, start2 and score for all observed points. 2) obs - the observed points. 3) exp - the expected points.

Examples

# Set misha db to test
gsetroot(shaman_get_test_track_db())
points <- gextract("hic_obs", gintervals.2d(2, 175.5e06, 177.5e06, 2, 175.5e06, 177.5e06), band = c(-2e06, -1024))
obs <- gextract("hic_obs", gintervals.2d(2, 175e06, 178e06, 2, 175e06, 178e06), band = c(-2e06, -1024))
exp <- gextract("hic_exp", gintervals.2d(2, 175e06, 178e06, 2, 175e06, 178e06), band = c(-2e06, -1024))
mat_score <- shaman_kk_norm(obs, exp, points, k = 100, k_exp = 200)
shaman_gplot_map_score(mat_score$points)

tanaylab/shaman documentation built on April 2, 2022, 1:32 a.m.