Infectious diseases pose a major threat to public health in all countries worldwide. Thus, new methods are needed to quickly identify known and unknown pathogens. DNA sequencing has shown to be an excellent tool for pathogen detection and pathogen characterization, like finding antibiotic resistance genes. In particular, the time to detection plays a vital role in clinical diagnostics. Therefore, we are developing various real-time tools to analyze DNA sequencing data. These generate intermediate results while the sequencing device processes the raw data. In such a way, we can decrease the time to report the detected pathogen (and antibiotic resistance gene), which can fasten diagnosis and accelerate the prescription of the correct medical treatment. Our tools utilize classical string comparison (HiLive2, PathoLive) and probabilistic data structures (ReadBouncer) for comparison with reference databases of known pathogens. We also develop Deep Learning methods (DeePaC, DeePaC-Live) that try to identify unknown pathogens. Our efforts in this field already resulted in patents and the founding of a spin-off (SEQSTANT), which offers holistic analysis for the diagnosis of pathogens from clinical samples. 

Our tools are freely accessible via the following links:

[HiLive2]  [PathoLive]  [ReadBouncer]  [DeePaC]  [DeePaC-Live]