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Fast and accurate average genome size and 16S rRNA gene average copy number computation in metagenomic data.

Emiliano Pereira-FloresFrank Oliver GlöcknerAntonio Fernandez-Guerra
Published in: BMC bioinformatics (2019)
We took advantage of recent advances in gene annotation to develop the ags.sh and acn.sh tools to combine easy tool usage with fast and accurate performance. Our tools compute the AGS and ACN metagenomic traits on unassembled metagenomes and allow researchers to improve their metagenomic data analysis to gain deeper insights into microorganisms' ecology. The ags.sh and acn.sh tools are publicly available using Docker container technology at https://github.com/pereiramemo/AGS-and-ACN-tools .
Keyphrases
  • copy number
  • genome wide
  • data analysis
  • mitochondrial dna
  • antibiotic resistance genes
  • dna methylation
  • high resolution
  • gene expression
  • machine learning
  • big data
  • wastewater treatment
  • genome wide identification