gatac doublets

Detect doublet / multiplet cells in a single-cell ATAC-seq sample using the AMULET Poisson method of Thibodeau et al. (2021). Cells with significantly more overlapping insertions than expected are flagged as doublets.

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Synopsis

gatac doublets <input.parquet> -g <genome> [-o OUTPUT]
                 [-m MIN_FRAGS] [--q Q] [--q-rep Q_REP]
                 [--expected-overlap N] [--max-insert N]
                 [--min-overlap N] [--repeat-filter BED]
                 [-j THREADS]

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Arguments

Positional

Argument	Description
input.parquet	Path to the fragment Parquet file

Options

Flag	Default	Description
-g, --genome	required	Genome name (hg38, mm10, …) or path to a chromosome sizes file
-o, --output	<input>_doublets.csv	Output CSV path
-m, --min-fragments	100	Minimum unique fragments per cell to include
--q	0.01	FDR threshold for doublet calling
--q-rep	0.01	FDR threshold for inferring repetitive regions
--expected-overlap	2	Expected number of reads overlapping (Poisson mean)
--max-insert	900	Maximum fragment insert size in bp
--min-overlap	1	Minimum overlap length in bp
--repeat-filter	—	BED file of known repetitive regions to exclude
-j, --threads	1	Parallel workers for overlap detection

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Output

A CSV with one row per cell:

Column	Description
cell_id	Cell barcode
p_value	Poisson p-value for the observed overlap count
q_value	Benjamini–Hochberg adjusted p-value
is_doublet	True if q_value < --q

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Examples

Basic usage

gatac doublets pbmc.parquet -g hg38 -o pbmc_doublets.csv

Stricter threshold

gatac doublets pbmc.parquet -g hg38 --q 0.001 -o pbmc_doublets.csv

Exclude known repetitive regions

gatac doublets pbmc.parquet -g hg38 --repeat-filter hg38_repeats.bed

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Python equivalent

import gatac as ga

result = ga.pp.detect_doublets(
    "pbmc.parquet",
    chrom_sizes="hg38",
    min_fragments=100,
    q_threshold=0.01,
)
print(result.head())
#   cell_id   p_value   q_value  is_doublet
# 0  AAAC...  0.8321   0.9412     False
# 1  AAAC...  0.0001   0.0034     True
# ...

# Drop doublets from an AnnData
doublets = set(result.loc[result["is_doublet"], "cell_id"])
adata = adata[~adata.obs_names.isin(doublets)].copy()

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Notes

AMULET’s Poisson model assumes a uniform single-copy background and is designed for autosomes only. Make sure the supplied chrom_sizes covers the autosomes of your species (the built-in hg38, hg19, mm10, mm39 aliases do).