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| Vận tốc RNA (RNA Velocity)× | Phân tích ATAC-seq× | |
|---|---|---|
| Lĩnh vực | Di truyền học | Di truyền học |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 2018 | 2013 |
| Người khởi xướng≠ | Gioele La Manno & Pavel Soldatov | Jason Buenrostro, Paul Giresi & William Greenleaf |
| Loại≠ | Trajectory inference method | Chromatin profiling method |
| Công trình gốc≠ | La Manno, G., Soldatov, R., Zeisel, A., Braun, E., Hochgerner, H., Petukhov, V., & Merad, M. (2018). RNA velocity of single cells. Nature, 560(7737), 494–498. DOI ↗ | Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013). Transposition of native chromatin for fast and sensitive epigenomic profiling of cell populations and tissues. Nature Methods, 10(12), 1213–1218. link ↗ |
| Tên gọi khác | Velocity analysis, Transcriptomic velocity, Cell fate prediction | Chromatin accessibility, Open chromatin, Accessible chromatin analysis |
| Liên quan | 2 | 2 |
| Tóm tắt≠ | RNA velocity is a computational method that infers the future developmental state of individual cells from single-cell RNA-sequencing data. Developed by La Manno and colleagues in 2018, RNA velocity analysis measures the direction and pace of cell state transitions by analyzing the ratio of unspliced to spliced mRNA transcripts within individual cells. This enables prediction of cell trajectories and differentiation pathways without requiring temporal sampling or manipulation, providing unique insights into cell fate decisions during development and disease. | ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) is a method for profiling the landscape of chromatin accessibility genome-wide. Developed by Buenrostro and colleagues in 2013, ATAC-seq uses hyperactive transposase to tag open, accessible chromatin regions, enabling rapid and sensitive identification of regulatory DNA elements. ATAC-seq has become a standard technique for characterizing gene regulatory landscapes, discovering cell-type-specific regulatory elements, and inferring gene regulatory networks. |
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