Science Score: 10.0%
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○Scientific vocabulary similarity
Low similarity (12.3%) to scientific vocabulary
Repository
Detect doublets in single-cell RNA-seq data
Basic Info
Statistics
- Stars: 155
- Watchers: 5
- Forks: 74
- Open Issues: 49
- Releases: 0
Metadata Files
README.md
Scrublet
Single-Cell Remover of Doublets
Python code for identifying doublets in single-cell RNA-seq data. For details and validation of the method, see our paper in Cell Systems or the preprint on bioRxiv.
Quick start:
For a typical workflow, including interpretation of predicted doublet scores, see the example notebook.
Given a raw (unnormalized) UMI counts matrix counts_matrix with cells as rows and genes as columns, calculate a doublet score for each cell:
python
import scrublet as scr
scrub = scr.Scrublet(counts_matrix)
doublet_scores, predicted_doublets = scrub.scrub_doublets()
scr.scrub_doublets() simulates doublets from the observed data and uses a k-nearest-neighbor classifier to calculate a continuous doublet_score (between 0 and 1) for each transcriptome. The score is automatically thresholded to generate predicted_doublets, a boolean array that is True for predicted doublets and False otherwise.
Best practices:
- When working with data from multiple samples, run Scrublet on each sample separately. Because Scrublet is designed to detect technical doublets formed by the random co-encapsulation of two cells, it may perform poorly on merged datasets where the cell type proportions are not representative of any single sample.
- Check that the doublet score threshold is reasonable (in an ideal case, separating the two peaks of a bimodal simulated doublet score histogram, as in this example), and adjust manually if necessary.
- Visualize the doublet predictions in a 2-D embedding (e.g., UMAP or t-SNE). Predicted doublets should mostly co-localize (possibly in multiple clusters). If they do not, you may need to adjust the doublet score threshold, or change the pre-processing parameters to better resolve the cell states present in your data.
Installation:
To install with PyPI:
bash
pip install scrublet
To install from source:
bash
git clone https://github.com/swolock/scrublet.git
cd scrublet
pip install -r requirements.txt
pip install --upgrade .
Old versions:
Previous versions can be found here.
Other doublet detection tools:
Owner
- Name: Sam Wolock
- Login: swolock
- Kind: user
- Location: Boston, MA
- Company: @dynotx
- Repositories: 1
- Profile: https://github.com/swolock
GitHub Events
Total
- Issues event: 6
- Watch event: 18
- Issue comment event: 6
- Fork event: 3
Last Year
- Issues event: 6
- Watch event: 18
- Issue comment event: 6
- Fork event: 3
Committers
Last synced: almost 3 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| swolock | s****k@g****m | 38 |
Issues and Pull Requests
Last synced: 12 months ago
All Time
- Total issues: 63
- Total pull requests: 3
- Average time to close issues: about 1 month
- Average time to close pull requests: 5 months
- Total issue authors: 59
- Total pull request authors: 2
- Average comments per issue: 1.46
- Average comments per pull request: 0.33
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 6
- Pull requests: 0
- Average time to close issues: 19 minutes
- Average time to close pull requests: N/A
- Issue authors: 6
- Pull request authors: 0
- Average comments per issue: 0.5
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- liliay (2)
- yingyonghui (2)
- victorwang123 (2)
- st4302 (2)
- TheSallyGardens (1)
- liron27 (1)
- RoganGrant (1)
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- rjg2186 (1)
- aopisco (1)
- AAA-3 (1)
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Pull Request Authors
- swolock (2)
- chris-rands (1)
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Issue Labels
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Packages
- Total packages: 1
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Total downloads:
- pypi 15,581 last-month
- Total docker downloads: 1,324
- Total dependent packages: 18
- Total dependent repositories: 20
- Total versions: 4
- Total maintainers: 1
pypi.org: scrublet
Doublet prediction in single-cell RNA-sequencing data
- Homepage: https://github.com/swolock/scrublet
- Documentation: https://scrublet.readthedocs.io/
- License: mit
-
Latest release: 0.2.3
published over 5 years ago
Rankings
Maintainers (1)
Dependencies
- annoy *
- matplotlib *
- numpy *
- scikit-learn *
- scipy *
- annoy *
- matplotlib *
- numpy *
- scikit-learn *
- scipy *
- annoy *
- cython *
- matplotlib *
- numba *
- numpy *
- pandas *
- scikit-image *
- scikit-learn *
- scipy *
- umap-learn *
- annoy *
- cython *
- matplotlib *
- numba *
- numpy *
- pandas *
- scikit-image *
- scikit-learn *
- scipy *
- umap-learn *