Epi-Gene: An R-Package for Easy Pan-Genome Analysis

Author:

Awan Furqan12ORCID,Ali Muhammad Muddassir3,Hamid Muhammad4ORCID,Awan Muhammad Huzair5,Mushtaq Muhammad Hassan2,Kalsoom Saeeda6,Ijaz Muhammad7,Mehmood Khalid8ORCID,Liu Yongjie1ORCID

Affiliation:

1. Joint International Research Laboratory of Animal Health and Food Safety, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China

2. Department of Epidemiology and Public Health, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan

3. Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan

4. Department of Statistics and Computer Sciences, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan

5. Computer Foundation Department, Cyber Brain Educational Institute, Lahore 54000, Pakistan

6. Department of Biotechnology, Virtual University of Pakistan, Lahore 54000, Pakistan

7. Department of Veterinary Medicine, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan

8. Faculty of Veterinary and Animal Sciences, The Islamia University of Bahawalpur, 63100, Pakistan

Abstract

The main aim of this study was to develop a set of functions that can analyze the genomic data with less time consumption and memory. Epi-gene is presented as a solution to large sequence file handling and computational time problems. It uses less time and less programming skills in order to work with a large number of genomes. In the current study, some features of the Epi-gene R-package were described and illustrated by using a dataset of the 14 Aeromonas hydrophila genomes. The joining, relabeling, and conversion functions were also included in this package to handle the FASTA formatted sequences. To calculate the subsets of core genes, accessory genes, and unique genes, various Epi-gene functions have been used. Heat maps and phylogenetic genome trees were also constructed. This whole procedure was completed in less than 30 minutes. This package can only work on Windows operating systems. Different functions from other packages such as dplyr and ggtree were also used that were available in R computing environment.

Funder

Priority Academic Program Development of Jiangsu Higher Education Institutions

Publisher

Hindawi Limited

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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