Automated Author ProfileBiobank Japan Project, The
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Biobank Japan Project, The
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.8 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Underrepresentation of non-European populations hinders growth of global precision medicine. Resources such as imputation reference panels that match the study population are necessary to find low-frequency variants with substantial effects. We created a reference panel consisting of 14,393 whole-genome sequences including more than 11,000 Asian individuals. Genome-wide association studies were conducted using the reference panel and a population-specific genotype array of 72K subjects for eight phenotypes. This panel yields improved imputation accuracy of rare and low-frequency variants within East Asian populations compared with the largest reference panel. Thirty-nine previously unidentified associations were found, and more than half of the variants were East-Asian-specific. We discovered genes with rare protein-altering variants, including LTBP1 for height and GPR75 for body mass index, as well as putative regulatory mechanisms for rare noncoding variants with cell-type-specific effects. We suggest this data set will add to the potential value of Asian precision medicine.
Authors
- Choi, Jaeyong ;
- Kim, Sungjae ;
- Kim, Juhyun ;
- Son, Ho-Young ;
- Yoo, Seong-Keun ;
- Kim, Chang-Uk ;
- Park, Young Jun ;
- Moon, Sungji ;
- Cha, Bukyoung ;
- Jeon, Min Chul ;
- Park, Kyunghyuk ;
- Yun, Jae Moon ;
- Cho, Belong ;
- Kim, Namcheol ;
- Kim, Changhoon ;
- Kwon, Nak-Jung ;
- Park, Young Joo ;
- Matsuda, Fumihiko ;
- Momozawa, Yukihide ;
- Kubo, Michiaki ;
- Biobank Japan Project, The ;
- Kim, Hyun-Jin ;
- Park, Jin-Ho ;
- Seo, Jeong-Sun ;
- Kim, Jong-Il ;
- Im, Sun-Wha