BarcodingR: an integrated r package for species identification using DNA barcodes

被引:43
|
作者
Zhang, Ai-bing [1 ]
Hao, Meng-di [1 ]
Yang, Cai-qing [1 ]
Shi, Zhi-yong [1 ]
机构
[1] Capital Normal Univ, Coll Life Sci, Beijing 100048, Peoples R China
来源
METHODS IN ECOLOGY AND EVOLUTION | 2017年 / 8卷 / 05期
关键词
artificial intelligence; barcodes evaluation; BP-based species identification; DNA barcoding; DNA barcoding gaps; DNA taxonomy; fuzzy-set-theory-based approach; species identification; CLASSIFICATION; SEQUENCES; SOFTWARE; GAP; MEMBERSHIP; EVOLUTION; DISCOVERY; ALIGNMENT; SET;
D O I
10.1111/2041-210X.12682
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Species identification via DNA barcodes has recently become an important and routine task in many biodiversity projects using DNA sequence data. Here, we present BarcodingR, an integrated software package that provides a comprehensive implementation of species identification methods, including artificial intelligence, fuzzy-set, Bayesian and kmer-based methods, that are not readily available in other packages. BarcodingR additionally provides new functions for barcode evaluation, barcoding gap analysis, delimitation comparison analysis, species membership analysis and consensus identification. Comparison with other barcoding methods using 11 empirical data sets indicates that on average, FZKMER (implemented in BarcodingR) and one extant barcoding method BRONX outperform all other methods examined in this study. Two other methods, BP and FZ (both implemented in BarcodingR), present similar performance as SVM and BLOG, respectively, and all display better performance than that of Jrip. The software of BarcodingR is open source under GNU General Public License and freely available for all major operating systems.
引用
收藏
页码:627 / 634
页数:8
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