Rapid development in technologies to read genomes has opened up unprecedented possibilities to discover links between our genomes and our health, quantitative traits and genetic ancestry. However, the massive amount of genomics data and limited understanding of its meaning at the level of individual make these goals challenging. To push the field forward we need truly interdisciplinary teamwork across medical, biological and computational sciences. Novel quantitative methods and new generations of quantitative scientists are a crucial part of continuing success in human genomics.
Our goal is to answer biologically and medically important questions quantitatively using data from our large Finnish cohorts and international collaborations. This requires 1) understanding the properties and context of the data, 2) identifying appropriate statistical approaches and 3) designing computational implementations that work in practice. Typically our main challenge is to determine a balance between the level of complexity of the statistical models and their computational tractability. We publish both new statistical methods as well as their applications on large data sets.