bin_motifs: Calculate Motif Membership Probabilty per chromatin loop

In NElnour/annotator3D: Classification of genome motifs or features to TADs

Description

Assuming equal chance of assignment given the matched sequence, this function calculates membership proportion of motifs per chromatin loop.

Usage

bin_motifs(motifs, chromLoops, j, M, m)

Arguments

motifs	A dataframe of matched motifs with at least the following attributes: start: an integer denoting the starting coordinate of matched motif stop: an integer denoting the end coordinate of matched motif
chromLoops	A row of a dataframe containing hierarchically clustered chromatin loops. Compatible with output of the annotator3D::cluster function. The row should have at least the following attributes: start: an integer denoting the starting coordinate of the predicted chromatin loop stop: an integer denoting the end coordinate of the predicted chromatin loop
j	An integer denoting the index of the chromatin loop for classification
M	An n-by-m numeric matrix to be used as a dynamic array of one chromatin loop.
m	An integer denoting the number of predicted loops.

Value

M An n-by-m numeric matrix storing calculated membership scores.

NElnour/annotator3D documentation built on Dec. 8, 2019, 9:22 a.m.