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:
- Publication Date:
- Research Org.:
- Colorado State Univ., Fort Collins, CO (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF); USDA National Inst. of Food and Agriculture (NIFA)
- OSTI Identifier:
- 1618579
- Alternate Identifier(s):
- OSTI ID: 1502978
- Grant/Contract Number:
- SC0012459; FG02-08ER64629; DEB-1556262; 2014–38420-21801
- Resource Type:
- Published Article
- Journal Name:
- BioData Mining
- Additional Journal Information:
- Journal Name: BioData Mining Journal Volume: 10 Journal Issue: 1; Journal ID: ISSN 1756-0381
- Publisher:
- Springer Science + Business Media
- Country of Publication:
- United Kingdom
- 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 Kingdom: 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 Kingdom. https://doi.org/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 Kingdom. https://doi.org/10.1186/s13040-017-0158-0.
@article{osti_1618579,
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 = 1,
volume = 10,
place = {United Kingdom},
year = {Tue Dec 19 00:00:00 EST 2017},
month = {Tue Dec 19 00:00:00 EST 2017}
}
https://doi.org/10.1186/s13040-017-0158-0
Web of Science
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