Classification of Functional Metagenomes Recovered from Different Environmental Samples

Classification of functional metagenomes from the microbial community plays the vital role in the metagenomics research. In this paper, an investigation was made to study the performance of beta-t random forest classifier for classification of metagenomics data. Nine key functional meta-genomic vari...

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Bibliographic Details
Published in:Bioinformation 2019-01, Vol.15 (1), p.26-31
Main Authors: Akond, Zobaer, Hasan, Mohammad Nazmol, Alam, Md Jahangir, Alam, Munirul, Mollah, Md Nurul Haque
Format: Article
Language:English
Subjects:
Bayesian analysis
Classification
Classifiers
Communities
Machine learning
Mathematical analysis
Microorganisms
Statistical methods
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Summary:Classification of functional metagenomes from the microbial community plays the vital role in the metagenomics research. In this paper, an investigation was made to study the performance of beta-t random forest classifier for classification of metagenomics data. Nine key functional meta-genomic variables were selected using the beta-t test statistic from the 10 different microbial community using p-value at 5% level of significance. Then beta-t random forest classifier showed the higher accuracy (96%), true positive rate (96%) and lower false positive rate (5%), false discovery rate (5%) and misclassification error rate (5%) for classification of metagenomes. This method showed the better performance compare to Bayes, SVM, KNN, AdaBoost and LogitBoost).
ISSN:0973-2063
0973-8894
0973-2063
DOI:10.6026/97320630015026