Markov chains improve the significance computation of overlapping genome annotations.

ABSTRACT:

Motivation

Genome annotations are a common way to represent genomic features such as genes, regulatory elements or epigenetic modifications. The amount of overlap between two annotations is often used to ascertain if there is an underlying biological connection between them. In order to distinguish between true biological association and overlap by pure chance, a robust measure of significance is required. One common way to do this is to determine if the number of intervals in the reference annotation that intersect the query annotation is statistically significant. However, currently employed statistical frameworks are often either inefficient or inaccurate when computing P-values on the scale of the whole human genome.

Results

We show that finding the P-values under the ty

SUBMITTER: Gafurov A 

PROVIDER: S-EPMC9235476 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature