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Study of Population Structure and Genetic Prediction of Buffalo from Different Provinces of Iran using Machine Learnin...
ISSN: 1927 - 520X
Publisher: author
Study of Population Structure and Genetic Prediction of Buffalo from Different Provinces of Iran using Machine Learnin...
Indexed in
Agriculture and Food Sciences
ARTICLE-FACTOR
1.3
Article Basics Score: 2
Article Transparency Score: 3
Article Operation Score: 2
Article Articles Score: 2
Article Accessibility Score: 3
SUBMIT PAPER ASK QUESTION
International Category Code (ICC):
ICC-0202
Publisher: Lifescience Global Inc.
International Journal Address (IAA):
IAA.ZONE/192710555520X
eISSN
:
1927 - 520X
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Abstract
Considering breeding livestock programs to milk production and type traits based on existence two different ecotypes of Iranian’s buffalo, a study carried out to investigate the population structure of Iranian buffalo and validate its classification accuracy according to different ecotypes from Iran (Azerbaijan and North) using data SNP chip 90K by means Support vector Machine (SVM), Random Forest (RF) and Discriminant Analysis Principal Component (DAPC) methods. A total of 258 buffalo were sampled and genotyped. The results of admixture, multidimensional scaling (MDS), and DAPC showed a close relationship between the animals of different provinces. Two ecotypes indicated higher accuracy of 96% that the Area Under Curve (AUC) confirmed the obtained result of the SVM approach while the DAPC and RF approach demonstrated lower accuracy of 88% and 80 %, respectively. SVM method proved high accuracy compared with DAPC and RF methods and as...
