2017 Fiscal Year Annual Research Report
Medical Sequence Classifier - a system for quick and accurate sequence-based diagnostics
| Project/Area Number |
17H07123
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| Research Institution | Tokai University |
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Principal Investigator |
クリュコフ キリル 東海大学, 医学部, 奨励研究員 (20806202)
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| Project Period (FY) |
2017-08-25 – 2019-03-31
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| Keywords | medical metagenomics |
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| Outline of Annual Research Achievements |
In the first year of this project I have developed a computational pipeline for analyzing medical metagenomic DNA datasets. This system allows identifying microbial pathogen species and strains in sequence datasets with high accuracy. Bacterial, fungal and other pathogens can be identified, allowing to diagnose broad range of diseases. This system can analyze sequences from a range of sequencers, including MinION, Ion PGM and MiSeq. It can be used on a computers from laptop to supercomputer. The pipeline produces text and graphical reports that can be used for making a diagnosis. In our lab and in collaboration with Tokai Universirty clinicians we applied this pipeline to investigating several clinical sequence datasets, that include both bacterial and fungal infections. This system proved helpful for detecting the pathogenic species and strains, and for diagnosing challenging cases. We also applied this pipeline for detecting virus DNA integrations in eukaryote genomes. The pipeline uses the GenomeSync database as reference, which allows access to latest genomic data. Currently the pipeline is undergoing further development and tests in collaboration with Tokai University researchers and medical doctors.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
The project is progressing without issues. Last year we published a paper related to this project, and a second paper is currently in press. I also presented this work in scientific conferences. The sequence classification pipeline developed in this project is highly regarded for accuracy among my collaborators. We have already investigated dozens of samples from infectious disease patients using my sequence classification system. Further development and testing is underway, including using additional clinical samples.
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| Strategy for Future Research Activity |
I am continuing the work on developing my sequence classification system. This year I will work on work on: improving classification accuracy, improving detection of contamination, adding detection of drug resistance. I am also continuing developing GenomeSync - the reference database used by my system. I will continue collaborative studies with Tokai University researchers and medical doctors, to further test and validate the pipeline. I will make my classifier system available and I will publish my results in a peer-reviewed journal.
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