Make data speak in rare childhood epilepsies

Capturing data. While genetic analysis can be performed and investigated on an industrial scale in thousands of individuals in parallel, the analysis of clinical data is frequently still the domain of manual data curation. Clinical data is typically collected in a non-standardized way, which makes it difficult for information generated in a clinical context to be used in a systematic data analysis as can be performed with genomic data. However, the tide is turning, and we are slowly coming around to the idea that clinical data also requires the same degree of standardization in order to be used at scale. For none of the epilepsies is such standardization more important than for the rare epilepsies, which include many of the genetic epilepsies. Our lab has been working on frameworks and methods to allow for this kind of analysis in genetic epilepsies. Here is a brief summary of what it actually means to “make data speak”, which has become the mission statement of our lab. Continue reading

Big data, ontologies, and the phenotypic bottle neck in epilepsy research

Unconnected data. Within the field of biomedicine, large datasets are increasingly emerging. These datasets include the genomic, imaging, and EEG datasets that we are somewhat familiar with, but also many large unstructured datasets, including data from biomonitors, wearables, and the electronic medical records (EMR). It appears that the abundance of these datasets makes the promise of precision medicine tangible – achieving an individualized treatment that is based on data, synthesizing available information across various domains for medical decision-making. In a recent review in the New England Journal of Medicine, Haendel and collaborators discuss the need in the biomedical field to focus on the development of terminologies and ontologies such as the Human Phenotype Ontology (HPO) that help put data into context. This review is a perfect segue to introduce the increasing focus on computational phenotypes within our group in order to overcome the phenotypic bottleneck in epilepsy genetics. Continue reading