About

About#

Data Science platform (DSP) from DTU - Biosustain organizes each Spring data-type courses for its research fellows of DTU Biosustain, Bioengineering and National Food Institute.

In 2025 edition we had one-day courses about:

  • Metagenomics

  • Transcriptomics

  • Proteomics

Metagenomics course objectives#

Theoretical#

  • Microbiome importance and application

  • Experimental design: from sample acquisition to abundance tables

  • Technology

    • 16S RNA amplification

    • Shotgun metagenomics

      • Reference-based

      • Metagenome assembled genomes (MAGs)

  • Diversity measuremets

  • Compositionality issues

  • Microbial gene catalogs

  • Functional analysis

Hands on#

  • Sample processing with nf-core/taxprofiler using Metaphlan database

  • Taxonomical overviews (stacked barplots)

  • Diversity measures

  • Sample distances

  • Principal coordinate analysis (PCoA) based on sample dissimilarity

  • Group comparison

    • Abundance comparison by Boxplots

    • Abundance comparison by Heatmap

  • Microbial Association Networks (MAN)

  • Reporting with vuegen

Data Science platform#

Data Science has become an essential piece both in academia and industry to accelerate gaining insights into the generated datasets. As a strategy to integrate high-level analytics in DTU - Biosustain we created a centralized Data Science platform (DSP) that provides support to our researchers while promoting standardized data and data processes.

The DSP team aims to make data science more accessible and inclusive not only at DTU Biosustain but also across the DTU Community. The platform follows a data-centric approach that focuses on data infrastructure, processes, and outputs as ongoing, evolving products rather than one-time projects. Each data product is designed as a multidisciplinary collaboration involving the entire data lifecycle and pursuing standardization and automation, and with data usage and reusage in mind.

The DSP is based on four pillars:

– Support: our research fellows on Statistics, Programming, Data analytics, and Machine learning

– Education: coorganizing Data club with DTU - Bioengineering and organizing Data Science workshops

– Innovation: introducing researchers to new computational biology methods and technologies

– Tooling: implementing open-sourced standard tools

You can contact us at Data Science platform email.

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