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Biostatistics - Bioinformatics

EXPOsOMICS has created a dedicated data infrastructure by building on existing data repositories to avoid redundancy. 

Data analysis, processing and integration

We have defined query methods, workflows for quality control, data harmonization and normalization in order to make all the data available for integrated analysis. Data integration includes five types of data:

  1. data from existing databases (e.g. OMI, diXA, CTDB);
  2. external exposure data from experimental/observational population studies;
  3. untargeted omic data;
  4. health information from cohorts, in different age groups;
  5. other exposures from cohorts (confounders, effect modifiers).

The complexity of the project design and data collected poses new methodological and analytical data challenges. Main such challenges are:

  • developing data analytics to address multiple exposures (both external and internal) in exposome-phenome association studies;
  • identification of statistical tools to address the hierarchical structure within external and internal exposure data (e.g. cross-omics analyses);
  • implementation of analytical tools to address the dynamics of the exposome-phenome associations over life.

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