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gNOMO: a multi-omics pipeline for integrated host and microbiome analysis of non-model organisms.

Maria Muñoz-BenaventFelix HartkopfTim Van Den BosscheVitor C PiroCarlos García-FerrisAmparo LatorreBernhard Y RenardThilo Muth
Published in: NAR genomics and bioinformatics (2020)
The study of bacterial symbioses has grown exponentially in the recent past. However, existing bioinformatic workflows of microbiome data analysis do commonly not integrate multiple meta-omics levels and are mainly geared toward human microbiomes. Microbiota are better understood when analyzed in their biological context; that is together with their host or environment. Nevertheless, this is a limitation when studying non-model organisms mainly due to the lack of well-annotated sequence references. Here, we present gNOMO, a bioinformatic pipeline that is specifically designed to process and analyze non-model organism samples of up to three meta-omics levels: metagenomics, metatranscriptomics and metaproteomics in an integrative manner. The pipeline has been developed using the workflow management framework Snakemake in order to obtain an automated and reproducible pipeline. Using experimental datasets of the German cockroach Blattella germanica, a non-model organism with very complex gut microbiome, we show the capabilities of gNOMO with regard to meta-omics data integration, expression ratio comparison, taxonomic and functional analysis as well as intuitive output visualization. In conclusion, gNOMO is a bioinformatic pipeline that can easily be configured, for integrating and analyzing multiple meta-omics data types and for producing output visualizations, specifically designed for integrating paired-end sequencing data with mass spectrometry from non-model organisms.
Keyphrases
  • data analysis
  • single cell
  • mass spectrometry
  • electronic health record
  • high resolution
  • machine learning
  • long non coding rna
  • binding protein
  • clinical evaluation