| Autor: |
Chachrit Khunsriraksakul, Daniel McGuire, Renan Sauteraud, Fang Chen, Lina Yang, Lida Wang, Jordan Hughey, Scott Eckert, J. Dylan Weissenkampen, Ganesh Shenoy, Olivia Marx, Laura Carrel, Bibo Jiang, Dajiang J. Liu |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Nature Communications, Vol 13, Iss 1, Pp 1-15 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2041-1723 |
| DOI: |
10.1038/s41467-022-30956-7 |
| Popis: |
Transcriptome-wide association studies can be used to test the effects of predicted gene expression in a cohort of individuals based on genetic data. Here, the authors developed a transcriptome-wide association method that integrates 3D genomic and epigenomic data with expression quantitative trait loci to improve gene expression predictions. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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