TopicVelo is a novel approach for RNA velocity inference in general systems, including immune
response studies. It infers the cells and genes associated with distinct active processes
via probabilistic topic modeling, and uses these to estimate process-specific velocity
parameters and transition probabilities, which are then integrated into large-scale transition
matrices. Parameter accuracy is also improved by efficiently fitting unsmoothed counts to a
transcriptional burst model. In biologically varied datasets, this approach outperformed the
state-of-the-art method, recovering parameters and transitions that were better experimentally
supported or recovered previously only with the aid of metabolic labeling or multiple time points.
For more information please see our preprint
(https://www.biorxiv.org/content/10.1101/2023.06.13.544828v1.full)
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Release files for topicvelo 0.0.2
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Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| topicvelo-0.0.2.tar.gz | 29.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| topicvelo-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 62.3 kB
Release files / topicvelo-0.0.2.tar.gz
| Download URL | topicvelo-0.0.2.tar.gz |
|---|---|
| Size | 29.9 kB |
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Release files / topicvelo-0.0.2-py3-none-any.whl
| Download URL | topicvelo-0.0.2-py3-none-any.whl |
|---|---|
| Size | 32.4 kB |
| Tags | Python 3 |
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