Description Usage Arguments Value
See preprint: Scrublet: computational identification of cell doublets in single-cell transcriptomic data Samuel L Wolock, Romain Lopez, Allon M Klein. bioRxiv 357368; doi: https://doi.org/10.1101/357368
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data |
expression matrix |
python_home |
The python home directory where Scrublet is installed |
return_results_only |
bool (optional, default False) |
min_counts, |
int (optional, default=2), See scrublet reference |
min_cells, |
int (optional, default=3), See scrublet reference |
expected_doublet_rate, |
float (optional, default=0.1), See scrublet reference - expected_doublet_rate: the fraction of transcriptomes that are doublets, typically 0.05-0.1. Results are not particularly sensitive to this parameter. For this example, the expected doublet rate comes from the Chromium User Guide: https://support.10xgenomics.com/permalink/3vzDu3zQjY0o2AqkkkI4CC |
min_gene_variability_pctl, |
int (optional, default=85), See scrublet reference |
n_prin_comps, |
int (optional, default=30), See scrublet reference (Number of principal components to use) |
sim_doublet_ratio, |
int (optional, default=2), the number of doublets to simulate, relative to the number of observed transcriptomes. This should be high enough that all doublet states are well-represented by simulated doublets. Setting it too high is computationally expensive. The default value is 2, though values as low as 0.5 give very similar results for the datasets that have been tested. |
n_neighbors, |
int (optional) n_neighbors: Number of neighbors used to construct the KNN classifier of observed transcriptomes and simulated doublets. The default value of round(0.5*sqrt(n_cells)) generally works well. Return only a list containing scrublet output |
The doublet_score output from scrublet,
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