Lazypipe is a bioinformatic pipeline for analyzing Next Generation Sequence (NGS) data. The main emphasis is on virus and bacterial metagenomics.

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.


Lazypipe supports

  • fastq preprocessing
  • host genome filtering
  • de novo assembling
  • taxonomic binning
  • taxonomic profiling
  • reporting
    • mapped contigs sorted by taxa
    • virus contigs
    • unmapped contigs
    • contig annotations (tsv and excel)
    • taxon abundancies in table format (tsv and excel)
    • taxon abundancies in KronaGraph format
    • quality control plots


Lazypipe can be quickly assessed using a preinstalled module at the Finnish Center of Scientific Computing.
To start using Lazypipe module on CSC Puhti server type:

module load r-env-singularity biokit lazypipe

All code and updates are available at Lazypipe repository.

Evaluation and benchmarking

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.

Results for OPAL evaluation of Lazypipe v1.1, Kraken2, MetaPhlan2 and Centrifuge on the MetaShot simulated metagenome are available here: (1) predicted virus taxa, (2) all predicted taxa.

Lazypipe v1.1 benchmarking on the mock-community data is available here: (3) mock-community results.


Citing Lazypipe

[1] 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.