Embeddings of genomic region sets capture rich biological associations in lower dimensions.

ABSTRACT:

Motivation

Genomic region sets summarize functional genomics data and define locations of interest in the genome such as regulatory regions or transcription factor binding sites. The number of publicly available region sets has increased dramatically, leading to challenges in data analysis.

Results

We propose a new method to represent genomic region sets as vectors, or embeddings, using an adapted word2vec approach. We compared our approach to two simpler methods based on interval unions or term frequency-inverse document frequency and evaluated the methods in three ways: First, by classifying the cell line, antibody or tissue type of the region set; second, by assessing whether similarity among embeddings can reflect simulated random perturbations of genomic regions; and th

SUBMITTER: Gharavi E 

PROVIDER: S-EPMC8652032 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature