Yosuke Tanigawa is a Ph.D. candidate in Biomedical Informatics program at Stanford University. His research interests are in various topics in population genomics, specifically focusing on the analysis of large-scale datasets.
Please check CV, Publications, and/or Google Scholar profile for list of publications and pre-prints. Please also check Resources page for datasets, analysis and visualization scripts, and web applications from our research activities (mainly from the Rivas lab and the Bejerano lab).
- Application of statistical genetics for human disease genetic studies. I am specifically interested in the analysis of population biobanks.
- Statistical and computational method development for large-scale datasets in the context of human genomic studies.
- Functional analysis of non-coding regions in the human genome. I am specifically interested in the analysis of transcription factors.
- 2021/1/18: New Publication. “Genetics of 35 blood and urine biomarkers in the UK Biobank”. In this project co-led by Nasa Sinnott-Armstrong, myself, and Dr. Manuel A. Rivas, we performed large-scale characterization of the genetic basis of biomarkers and cataloged their influence on diseases. We developed the ‘multi-PRS’ method and demonstrated its improved ability of disease prediction. Please check out highlights and the full texts.
- 2021/2/16: New Manuscript. We have a new preprint led by Ruilin Li describing a new version of the R snpnet package and its application to the exome sequencing data in UK Biobank: “Fast Numerical Optimization for Genome Sequencing Data in Population Biobanks”.
- 2021/2/9: New Publications. We have two papers from the Rivas lab. Yosuke contributed to each of them as the second author and is very excited to see them published! Congratulations, Matt and Ruilin!
- News Archive:
Email is the best contact to reach out to me. If you do not get a reply within two days, please do not hesitate to follow-up. Thank you very much for your interest in our work.
yosuke <dot> tanigawa [at] stanford <dot> edu
- Social media accounts can be found on the left (for PC) or “Follow” button on the top (for smartphone).