MADRONE: USER-FRIENDLY BIOINFORMATICS PLATFORM FOR CLUSTER ANALYSIS
Researchers at the Chan Zuckerberg Biohub have developed advanced analytics for pathogen infection tracking and control.
Health officials use genomic sequence information for both identification and tracking of infectious disease outbreaks. However, most epidemiological analysis of pathogen sequence information in the United States is through rudimentary software tools such as spreadsheets. Tracking of millions of nucleotide sequences using rudimentary tools is cumbersome and error-prone, and limits extracting actionable information such as date and geographical location.
Stage of Research
The inventors have developed Madrone, a user-friendly bioinformatics platform for processing and visualizing medical and genomic data corresponding to pathogens (e.g., bacteria, viruses, fungi). Their user-interface and backend computer systems provide a comprehensive view of pathogen presence based on analyzing sequences of biological samples collected from several facilities and regions. By facilitating analysis of the biological samples, infectious disease outbreaks can be detected and tracked, and pathogens causing the infection disease outbreaks can be identified.
Applications
- Manage and analyze files corresponding to biological samples and their respective nucleotide sequences
- Visualization and clustering of biological samples that have similar nucleotide sequences to track and control infectious disease outbreaks
- Detection and identification of pathogens at a particular geographic region
Advantages
- Medical and genomic data of pathogens collected from different regions can be stored in a database server
- User access control can protect unauthorized exposure of sensitive medical data by anonymizing and de-identifying sensitive information
- Multi-functional user interface to access, identify, and analyze relationships between genomic sequences of deposited biological samples, including hierarchical clutering, dendrograms and similarity matrices
Publications
PCT Publication WO2021092231
Keywords
Bacterial and viral pathogenesis, epidemiology
Technology Reference
CZB-137
