Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Markov chains improve the significance computation of overlapping genome annotations

Askar Gafurov, View ORCID ProfileBroňa Brejová, Paul Medvedev
doi: https://doi.org/10.1101/2022.04.07.487119
Askar Gafurov
1Department of Computer Science, Comenius University, Bratislava, 84248, Slovakia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: askar.gafurov@fmph.uniba.sk
Broňa Brejová
1Department of Computer Science, Comenius University, Bratislava, 84248, Slovakia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Broňa Brejová
Paul Medvedev
2Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA 16802, USA
3Department of Biochemistry and Molecular Biology, The Pennsylvania State University, PA 16802, USA
4Huck Institutes of the Life Sciences, The Pennsylvania State University, PA 16802, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

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 typically used “gold” null hypothesis is 𝒩𝒫-hard. This motivates us to reformulate the null hypothesis using Markov chains. To be able to measure the fidelity of our Markovian null hypothesis, we develop a fast direct sampling algorithm to estimate the p-value under the gold null hypothesis. We then present an open-source software tool MCDP that computes the p-values under the Markovian null hypothesis in 𝒪 (m2 + n) time and 𝒪 (m) memory, where m and n are the numbers of intervals in the reference and query annotations, respectively. Notably, MCDP runtime and memory usage are independent from the genome length, allowing it to outperform previous approaches in runtime and memory usage by orders of magnitude on human genome annotations, while maintaining the same level of accuracy.

Availability The software is available at https://github.com/fmfi-compbio/mc-overlaps. All data for reproducibility are available at https://github.com/fmfi-compbio/mc-overlaps-reproducibility

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/fmfi-compbio/mc-overlaps

  • https://github.com/fmfi-compbio/mc-overlaps-reproducibility

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted April 10, 2022.
Download PDF
Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Markov chains improve the significance computation of overlapping genome annotations
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Markov chains improve the significance computation of overlapping genome annotations
Askar Gafurov, Broňa Brejová, Paul Medvedev
bioRxiv 2022.04.07.487119; doi: https://doi.org/10.1101/2022.04.07.487119
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Markov chains improve the significance computation of overlapping genome annotations
Askar Gafurov, Broňa Brejová, Paul Medvedev
bioRxiv 2022.04.07.487119; doi: https://doi.org/10.1101/2022.04.07.487119

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4675)
  • Biochemistry (10347)
  • Bioengineering (7659)
  • Bioinformatics (26307)
  • Biophysics (13505)
  • Cancer Biology (10672)
  • Cell Biology (15424)
  • Clinical Trials (138)
  • Developmental Biology (8490)
  • Ecology (12808)
  • Epidemiology (2067)
  • Evolutionary Biology (16835)
  • Genetics (11383)
  • Genomics (15471)
  • Immunology (10603)
  • Microbiology (25186)
  • Molecular Biology (10211)
  • Neuroscience (54399)
  • Paleontology (400)
  • Pathology (1667)
  • Pharmacology and Toxicology (2889)
  • Physiology (4334)
  • Plant Biology (9237)
  • Scientific Communication and Education (1586)
  • Synthetic Biology (2556)
  • Systems Biology (6774)
  • Zoology (1461)