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

diploS/HIC: an updated approach to classifying selective sweeps

View ORCID ProfileAndrew D. Kern, View ORCID ProfileDaniel R. Schrider
doi: https://doi.org/10.1101/267229
Andrew D. Kern
Rutgers University, Department of Genetics, Piscataway, NJ, 08854, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Andrew D. Kern
  • For correspondence: kern@biology.rutgers.edu
Daniel R. Schrider
Rutgers University, Department of Genetics, Piscataway, NJ, 08854, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Daniel R. Schrider
  • For correspondence: kern@biology.rutgers.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Identifying selective sweeps in populations that have complex demographic histories remains a difficult problem in population genetics. We previously introduced a supervised machine learning approach, S/HIC, for finding both hard and soft selective sweeps in genomes on the basis of patterns of genetic variation surrounding a window of the genome. While S/HIC was shown to be both powerful and precise, the utility of S/HIC was limited by the use of phased genomic data as input. In this report we describe a deep learning variant of our method, diploS/HIC, that uses unphased genotypes to accurately classify genomic windows. diploS/HIC is shown to be quite powerful even at moderate to small sample sizes

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 February 18, 2018.
Download PDF
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.
diploS/HIC: an updated approach to classifying selective sweeps
(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
diploS/HIC: an updated approach to classifying selective sweeps
Andrew D. Kern, Daniel R. Schrider
bioRxiv 267229; doi: https://doi.org/10.1101/267229
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
diploS/HIC: an updated approach to classifying selective sweeps
Andrew D. Kern, Daniel R. Schrider
bioRxiv 267229; doi: https://doi.org/10.1101/267229

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

  • Evolutionary Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4086)
  • Biochemistry (8761)
  • Bioengineering (6479)
  • Bioinformatics (23340)
  • Biophysics (11750)
  • Cancer Biology (9149)
  • Cell Biology (13247)
  • Clinical Trials (138)
  • Developmental Biology (7416)
  • Ecology (11369)
  • Epidemiology (2066)
  • Evolutionary Biology (15087)
  • Genetics (10398)
  • Genomics (14009)
  • Immunology (9121)
  • Microbiology (22040)
  • Molecular Biology (8779)
  • Neuroscience (47366)
  • Paleontology (350)
  • Pathology (1420)
  • Pharmacology and Toxicology (2482)
  • Physiology (3704)
  • Plant Biology (8050)
  • Scientific Communication and Education (1431)
  • Synthetic Biology (2208)
  • Systems Biology (6016)
  • Zoology (1249)