השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ניתוח ATAC-seq× | מהירות RNA (RNA Velocity)× | |
|---|---|---|
| תחום | גנטיקה | גנטיקה |
| משפחה | Process / pipeline | Process / pipeline |
| שנת המקור≠ | 2013 | 2018 |
| הוגה השיטה≠ | Jason Buenrostro, Paul Giresi & William Greenleaf | Gioele La Manno & Pavel Soldatov |
| סוג≠ | Chromatin profiling method | Trajectory inference method |
| מקור מכונן≠ | 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 ↗ | 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 ↗ |
| כינויים | Chromatin accessibility, Open chromatin, Accessible chromatin analysis | Velocity analysis, Transcriptomic velocity, Cell fate prediction |
| קשורות | 2 | 2 |
| תקציר≠ | 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. | 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. |
| ScholarGateמערך נתונים ↗ |
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