Autosomal deletion/insertion polymorphisms for global stratification analyses and ancestry origin inferences of different continental populations by machine learning methods-Reference-Cited by-同舟云学术

Autosomal deletion/insertion polymorphisms for global stratification analyses and ancestry origin inferences of different continental populations by machine learning methods

Published:2021-05-19 Issue:14-15 Volume:42 Page:1473-1479
ISSN:0173-0835
Container-title:ELECTROPHORESIS
language:en
Short-container-title:ELECTROPHORESIS

Author:

Jin Xiaoye¹²³,Liu Yuluo⁴,Zhang Yuanyuan⁵,Li Yongle³,Chen Chuanliang⁶,Wang Hongdan²³^ORCID

Affiliation:

1. Department of Forensic Medicine Guizhou Medical University Guiyang P. R. China

2. Medical Genetics Institute of Henan Province Henan Provincial People's Hospital，Zhengzhou University People's Hospital Zhengzhou P. R. China

3. National Health Commission Key Laboratory of Birth Defects Prevention Henan Key Laboratory of Population Defects Prevention Zhengzhou P. R. China

4. Department of Forensic Science Guangdong Police College Guangzhou P. R. China

5. School of Foreign Languages Zhengzhou University of Industrial Technology Zhengzhou P. R. China

6. Henan Provincial People's Hospital Zhengzhou University People's Hospital Zhengzhou P. R. China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Clinical Biochemistry,Biochemistry,Analytical Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/elps.202100044

Reference36 articles.

1. Development of a novel multiplex polymerase chain reaction system for forensic individual identification using insertion/deletion polymorphisms

2. Developmental validation of a novel six-dye typing system with 47 A-InDels and 2 Y-InDels

3. Completion of a worldwide reference panel of samples for an ancestry informative Indel assay

4. Straightforward Inference of Ancestry and Admixture Proportions through Ancestry-Informative Insertion Deletion Multiplexing

5. Distinguishing three distinct biogeographic regions with an in‐house developed 39‐AIM‐InDel panel and further admixture proportion estimation for Uyghurs

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