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  • Correction
  • Open Access

Correction to: Application of geographic population structure (GPS) algorithm for biogeographical analyses of populations with complex ancestries: a case study of South Asians from 1000 genomes project

Contributed equally
BMC Genetics201819:96

https://doi.org/10.1186/s12863-018-0683-y

  • Published:

The original article was published in BMC Genetics 2017 18:109

Correction

Following publication of the original article [1], the authors flagged that acknowledgment of their equal contribution is omitted in the article [1].

As such, please be advised that both authors contributed equally to this work.

We apologize for this processing error.

Notes

Declarations

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Manipal Centre for Natural Sciences (MCNS), Manipal Academy of Higher Education, Madhav Nagar, Manipal, Karnataka, 576104, India
(2)
Department of Medical Genetics, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, India

Reference

  1. Das, et al. Application of geographic population structure (GPS) algorithm for biogeographical analyses of populations with complex ancestries: a case study of South Asians from 1000 genomes project. BMC Genet. 2017;18(Suppl 1):109. https://doi.org/10.1186/s12863-017-0579-2.View ArticlePubMedPubMed CentralGoogle Scholar

Copyright

© The Author(s). 2018

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