overlap_score: Ranks pairs of features by how much they overlap in a graph

In CamaraLab/AdjacencyScore: Computes a bivariate metric to rank pairs of features by how colocalized they are in a graph

Description

Given the adjacency matrix of a graph and a set of features on that graph, ranks given pairs of those features (f and g) by the equation fg, which measures how much those features cooccur in the same cells. Calculates the p-value for this score by permuting the columns of the feature matrix separately for each features.

Usage

overlap_score(f, f_pairs, num_perms = 1000, seed = 10, num_cores = 1,
  perm_estimate = F)

Arguments

f	a numeric matrix specifying one or more features defined for each node of the graph. Each column is a node of the graph and each row is a feature over the nodes.
f_pairs	a 2 column matrix where each row specifies the indices or names of a pair of features on which the score will be computed
num_perms	number of permutations used to build the null distribution for each feature. By default is set to 1000.
seed	integer specifying the seed used to initialize the generator of permutations. By default is set to 10.
num_cores	integer specifying the number of cores to be used in the computation. By default only one core is used.
perm_estimate	boolean indicating whether normal distribution parameters should be determined from num_perms permutations to estimate the p-value. By default is set to FALSE.

CamaraLab/AdjacencyScore documentation built on May 23, 2021, 12:57 p.m.