The study of microbiome data holds unlimited potential for outlining of the biological and metabolic functioning of living organisms and their role in the environment. With increase in the availability of metagenomic data in this era of Next Generation Sequencing (NGS) when the technologies are becoming cheaper than ever before, we urgently need reliable and comprehensive methods/pipelines for dealing with such data. In this paper we present a novel stand-alone pipeline called the LAZYPIPE for identifying viruses in host-associated and environmental samples.
module load r-env-singularity biokit lazypipe
All code and updates are available at Lazypipe repository.
Lazypipe releases v1.0 and v1.1 were benchmarked against three other software packages for taxonomic profiling. Benchmarking was performed with both simulated and real data. For a quick summary see our v1.0 benchmarking report.
Lazypipe v1.1 benchmarking on the mock-community data is available here: (3) mock-community results.
 Ilya Plyusnin, Ravi Kant, Anne J. Jaaskelainen, Tarja Sironen, Liisa Holm, Olli Vapalahti, Teemu Smura. (2020) Novel NGS Pipeline for Virus Discovery from a Wide Spectrum of Hosts and Sample Types. Virus Evolution, veaa091, https://doi.org/10.1093/ve/veaa091.