Predicting Geographic Location from Genetic Variation with Deep Neural Networks

Author:

Battey C.J.ORCID,Ralph Peter L.ORCID,Kern Andrew D.ORCID

Abstract

AbstractMost organisms are more closely related to nearby than distant members of their species, creating spatial autocorrelations in genetic data. This allows us to predict the location of origin of a genetic sample by comparing it to a set of samples of known geographic origin. Here we describe a deep learning method, which we call Locator, to accomplish this task faster and more accurately than existing approaches. In simulations, Locator infers sample location to within 4.1 generations of dispersal and runs at least an order of magnitude faster than a recent model-based approach. We leverage Locator’s computational efficiency to predict locations separately in windows across the genome, which allows us to both quantify uncertainty and describe the mosaic ancestry and patterns of geographic mixing that characterize many populations. Applied to whole-genome sequence data from Plasmodium parasites, Anopheles mosquitoes, and global human populations, this approach yields median test errors of 16.9km, 5.7km, and 85km, respectively.

Publisher

Cold Spring Harbor Laboratory

Reference65 articles.

1. Martín Abadi , Ashish Agarwal , Paul Barham , Eugene Brevdo , Zhifeng Chen , Craig Citro , Greg S. Corrado , Andy Davis , Jeffrey Dean , Matthieu Devin , Sanjay Ghemawat , Ian Goodfellow , Andrew Harp , Geoffrey Irving , Michael Isard , Yangqing Jia , Rafal Jozefowicz , Lukasz Kaiser , Manjunath Kudlur , Josh Levenberg , Dan Mané , Rajat Monga , Sherry Moore , Derek Murray , Chris Olah , Mike Schuster , Jonathon Shlens , Benoit Steiner , Ilya Sutskever , Kunal Talwar , Paul Tucker , Vincent Vanhoucke , Vijay Vasudevan , Fernanda Viégas , Oriol Vinyals , Pete Warden , Martin Wattenberg , Martin Wicke , Yuan Yu , and Xiaoqiang Zheng . TensorFlow: Large-scale machine learning on heterogeneous systems, 2015. URL http://tensorflow.org/. Software available from tensorflow.org.

2. Predicting the Landscape of Recombination Using Deep Learning

3. Characterization of Within-Host Plasmodium falciparum Diversity Using Next-Generation Sequence Data

4. Enhanced Localization of Genetic Samples through Linkage-Disequilibrium Correction

5. A migratory divide in the Painted Bunting (Passerina ciris);The American Naturalist,2018

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3