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

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 wi...

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Publicado en:BioMed Research International pp. 1 - 9
Autores principales: Awan, Furqan, Ali, Muhammad Muddassir, Hamid, Muhammad, Awan, Muhammad Huzair, Mushtaq, Muhammad Hassan, Kalsoom, Saeeda, Ijaz, Muhammad, Mehmood, Khalid, Liu, Yongjie
Formato: research tables/charts Journal Article
Publicado: Wiley-Blackwell 9/21/2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 9/21/2021
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2021/5585586
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        atl: Epi-Gene: An R-Package for Easy Pan-Genome Analysis.
      aug:
        au:
          Awan, Furqan
          Ali, Muhammad Muddassir
          Hamid, Muhammad
          Awan, Muhammad Huzair
          Mushtaq, Muhammad Hassan
          Kalsoom, Saeeda
          Ijaz, Muhammad
          Mehmood, Khalid
          Liu, Yongjie
        affil: Joint International Research Laboratory of Animal Health and Food Safety, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
      sug:
        subj:
          Epigenomics
          Time Factors
          Data Analysis, Statistical
          Computer Memory
          Human
          Genome
          Computers and Computerization
          Phylogenetics
          Software
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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