perform.scrublet: Python module: scrublet

In connorhknight/IBRAP_no_decontX: Integrated Benchmarking scRNA-seq Analytical Pipeline

Description

Removes doublets from dataset.

Usage

perform.scrublet(counts = counts, expected_doublet_rate = 0.025)

Arguments

counts	Counts matrix
save.plot	Boolean. Should the automatically genewrated plot be saved? Default = TRUE
total_counts	Total number of cells. NULL = automatically counts.
sim_doublet_ratio	Number of doublets to simulate relative to observed
n_neighbors	Expected number of neighbours per cell
expected_doublet_rate	Expected percentage of doublets to be present in the dataset
stdev_doublet_rate	Uncertainty in expected doublet rate
random_state	Random state for doublet simulation, approximate nearest neighbour search, nd PCA/Truncated PCA
synthetic_doublet_umi_subsampling	Sampling rate for UMIs in a cell when synthesising doublets
use_approx_neighbors	Use approximate nearest neighbor method '(annoy)' for the KNN classifier
distance_metric	Define distance metric for nearest neighbour calculation: 'angular', 'euclidean', 'manhattan', 'hamming', 'dot'.
get_doublet_neighbor_parents	return the transcriptomes of the parent cells for simulated doublets
min_counts	Minimum counts per cell
min_cells	Minimum number of cells per gene
min_gene_variability_pctl	Variability cutoff when deducing highly variable genes prior to PCA reduction
log_transform	Log transforms the data
mean_center	Should the dataset be centred around the mean
normalize_variance	Should the genes have a total variance of 1
n_prin_comps	Number of principal components to retain
svd_solver	Which SVD solver to use: 'auto', 'full', 'arpack', 'randomized'.

Value

Doublet-omitted sparse matrix

Examples

object <- perform.scrublet(counts = counts)

connorhknight/IBRAP_no_decontX documentation built on Feb. 13, 2022, 2:32 p.m.