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Title: TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps

Abstract

Recent advances in nucleic acid sequencing technologies have led to a dramatic increase in the number of markers available to generate genetic linkage maps. This increased marker density can be used to improve genome assemblies as well as add much needed resolution for loci controlling variation in ecologically and agriculturally important traits. However, traditional genetic map construction methods from these large marker datasets can be computationally prohibitive and highly error prone. We present TSPmap, a method which implements both approximate and exact Traveling Salesperson Problem solvers to generate linkage maps. We demonstrate that for datasets with large numbers of genomic markers (e.g. 10,000) and in multiple population types generated from inbred parents, TSPmap can rapidly produce high quality linkage maps with low sensitivity to missing and erroneous genotyping data compared to two other benchmark methods, JoinMap and MSTmap. TSPmap is open source and freely available as an R package. With the advancement of low cost sequencing technologies, the number of markers used in the generation of genetic maps is expected to continue to rise. TSPmap will be a useful tool to handle such large datasets into the future, quickly producing high quality maps using a large number of genomic markers.

Authors:
 [1];  [2];  [1];  [1];  [3];  [1];  [2];  [1]
  1. Colorado State Univ., Fort Collins, CO (United States). Dept. of Bioagricultural Sciences & Pest Management
  2. Colorado State Univ., Fort Collins, CO (United States). Dept. of Computer Sciences
  3. HudsonAlpha Inst. for Biotechnology, Huntsville, AL (United States)
Publication Date:
Research Org.:
Colorado State Univ., Fort Collins, CO (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Science Foundation (NSF); USDA National Inst. of Food and Agriculture (NIFA)
OSTI Identifier:
1502978
Grant/Contract Number:  
SC0012459; FG02-08ER64629; DEB-1556262; 2014–38420-21801
Resource Type:
Accepted Manuscript
Journal Name:
BioData Mining
Additional Journal Information:
Journal Volume: 10; Journal ID: ISSN 1756-0381
Publisher:
BMC, Springer Nature
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 59 BASIC BIOLOGICAL SCIENCES; genetic mapping; linkage; travelling salesperson problem; genomic markers; next generation sequencing; genotyping by sequencing

Citation Formats

Monroe, J. Grey, Allen, Zachariah A., Tanger, Paul, Mullen, Jack L., Lovell, John T., Moyers, Brook T., Whitley, Darrell, and McKay, John K.. TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps. United States: N. p., 2017. Web. doi:10.1186/s13040-017-0158-0.
Monroe, J. Grey, Allen, Zachariah A., Tanger, Paul, Mullen, Jack L., Lovell, John T., Moyers, Brook T., Whitley, Darrell, & McKay, John K.. TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps. United States. doi:10.1186/s13040-017-0158-0.
Monroe, J. Grey, Allen, Zachariah A., Tanger, Paul, Mullen, Jack L., Lovell, John T., Moyers, Brook T., Whitley, Darrell, and McKay, John K.. Tue . "TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps". United States. doi:10.1186/s13040-017-0158-0. https://www.osti.gov/servlets/purl/1502978.
@article{osti_1502978,
title = {TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps},
author = {Monroe, J. Grey and Allen, Zachariah A. and Tanger, Paul and Mullen, Jack L. and Lovell, John T. and Moyers, Brook T. and Whitley, Darrell and McKay, John K.},
abstractNote = {Recent advances in nucleic acid sequencing technologies have led to a dramatic increase in the number of markers available to generate genetic linkage maps. This increased marker density can be used to improve genome assemblies as well as add much needed resolution for loci controlling variation in ecologically and agriculturally important traits. However, traditional genetic map construction methods from these large marker datasets can be computationally prohibitive and highly error prone. We present TSPmap, a method which implements both approximate and exact Traveling Salesperson Problem solvers to generate linkage maps. We demonstrate that for datasets with large numbers of genomic markers (e.g. 10,000) and in multiple population types generated from inbred parents, TSPmap can rapidly produce high quality linkage maps with low sensitivity to missing and erroneous genotyping data compared to two other benchmark methods, JoinMap and MSTmap. TSPmap is open source and freely available as an R package. With the advancement of low cost sequencing technologies, the number of markers used in the generation of genetic maps is expected to continue to rise. TSPmap will be a useful tool to handle such large datasets into the future, quickly producing high quality maps using a large number of genomic markers.},
doi = {10.1186/s13040-017-0158-0},
journal = {BioData Mining},
number = ,
volume = 10,
place = {United States},
year = {2017},
month = {12}
}

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Works referenced in this record:

A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species
journal, May 2011