MoCoLo: a testing framework for motif co-localization.

ABSTRACT: Sequence-level data offers insights into biological processes through the interaction of two or more genomic features from the same or different molecular data types. Within motifs, this interaction is often explored via the co-occurrence of feature genomic tracks using fixed-segments or analytical tests that respectively require window size determination and risk of false positives from over-simplified models. Moreover, methods for robustly examining the co-localization of genomic features, and thereby understanding their spatial interaction, have been elusive. We present a new analytical method for examining feature interaction by introducing the notion of reciprocal co-occurrence, define statistics to estimate it and hypotheses to test for it. Our approach leverages conditional motif co

SUBMITTER: Xu Q 

PROVIDER: S-EPMC10960634 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature