Title

Classification of Functional Metagenomes Recovered from Different Environmental Samples

Authors

Zobaer Akond^{1, 2, 3,*}, Mohammad Nazmol Hasan^1,5, Md. Jahangir Alam¹, Munirul Alam⁴, Md. Nurul Haque Mollah⁵

Affiliation

¹Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi-6205, Bangladesh; ²Institute of Environmental Science, University of Rajshahi-6205, Bangladesh; ³Agricultural Statistics and Information & Communication Technology (ASICT) Division, Bangladesh Agricultural Research Institute (BARI), Joydebpur, Gazipur-1701, Bangladesh; ⁴Emerging Infections, Infectious Diseases
Division, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b); ⁵Bangabandhu Sheikh Mujibur Rahaman Agricultural University,Joydebpur,Gazipur-1706, Bangladesh.

Email

Zobaer Akond – E-mail:akond25@yahoo.com; *Corresponding Author

Article Type

Research Article

Date

Received December 13, 2018; Accepted December 26, 2018; Published January 31, 2019

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 & LogitBoost).

Keywords

metagenomes, classification, true positive rate, false positive rate, misclassification error, beta-t random forest

Citation

Received December 13, 2018; Accepted December 26, 2018; Published January 31, 2019

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.