megasat : automated inference of microsatellite genotypes from sequence data-Reference-Cited by-同舟云学术

megasat : automated inference of microsatellite genotypes from sequence data

Published:2016-07-19 Issue:2 Volume:17 Page:247-256
ISSN:1755-098X
Container-title:Molecular Ecology Resources
language:en
Short-container-title:Mol Ecol Resour

Author:

Zhan Luyao¹,Paterson Ian G.²,Fraser Bonnie A.³,Watson Beth²,Bradbury Ian R.⁴,Nadukkalam Ravindran Praveen¹,Reznick David⁵,Beiko Robert G.¹,Bentzen Paul²

Affiliation:

1. Faculty of Computer Science Dalhousie University 6050 University Avenue Halifax Nova Scotia B3H 4R2 Canada

2. Marine Gene Probe Laboratory Department of Biology Dalhousie University 1355 Oxford Street Halifax Nova Scotia B3H 4R2 Canada

3. Evolution Behaviour and Environment Group University of Sussex Sussex House Falmer Brighton BN1 9RH UK

4. Salmonids Section Science Branch Department of Fisheries and Oceans Canada 80 East White Hills Road St. John's Newfoundland A1C 5X1 Canada

5. Department of Biology University of California Riverside CA 92521 USA

Funder

Natural Sciences and Engineering Research Council of Canada

National Science Foundation

Publisher

Wiley

Subject

Genetics,Ecology, Evolution, Behavior and Systematics,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/1755-0998.12561

Reference23 articles.

1. Microsatellite data show recent demographic expansions in sedentary but not in nomadic human populations in Africa and Eurasia

2. Genotyping‐in‐Thousands by sequencing (GT‐seq): A cost effective SNP genotyping method based on custom amplicon sequencing

3. msatcommander: detection of microsatellite repeat arrays and automated, locus-specific primer design

4. Rise of the machines – recommendations for ecologists when using next generation sequencing for microsatellite development

5. Current trends in microsatellite genotyping

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