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CLI Reference

Main arguments

--input None
The path to your .h5ad or .rds file. Supports object: anndata, Seurat, SingleCellExperiment, SpatialExperiment. Note that the spatial coordinates of anndata objects are stored in obsm['spatial']. If your Seurat object does not have an images slot, the row and col coordinates need to be provided in meta.data. SingleCellExperiment must provide row and col coordinates.

--platform None
Platform of your spatial transcriptomics data. Visium, MERFISH, Stereo-seq, etc.
Visium: Same as --doublet False --n 0.95 --l 0.99 --s 4 --min_genes_list 0 200 400 600 800 1000 1200 --min_genes_list2 0 200 400 600 800 1000 1200 --min_cells_list 1 2 3 4 5. Or set the parameter to 'Slide-seq', 'ST', 'DBiT-seq'.
MERFISH: Same as --doublet True --n 0.9 --min_cells 1 --s 3 --min_genes_list 0 10 20 30 40 50 --min_genes_list2 0 10 20 30 40 50 --min_cells_list 1 --s2 0 0 1. Or set the parameter to 'Xenium', 'CosMx', 'HybISS'.
Stereo-seq: Same as --doublet True --n 0.7 --l 0.99 --s4 --min_genes_list 0 200 400 600 800 1000 1200 --min_genes_list2 0 200 400 600 800 1000 1200 --min_cells_list 0 10 20 30 40. Or set the parameter to 'Seq-scope', 'Pixel-seq', 'HDST', 'Visium HD'.

--slice_number multiple
The number of slices of .h5ad provided. multiple or 1.

--slice id
The name that represents the slice identifier in anndata.obs. If there is only one slice, ignore this parameter.

--mito 'Mt-'
The pattern of mitochondrial genes.

--ribo 'Rps, Rpl'
The pattern of ribosome genes.

--hemo 'Hbb, Hba'
The pattern of hemoglobin genes.

Marker genes arguments

--markers None
The path to your marker genes .csv file. You can obtain genes based on prior knowledge or DEGs from scRNA-seq of the same tissue.
We also provided mouse and human marker genes obtained from the cellmarker2.0 database. If you don't have a suitable markers file, you can specify the parameters --species, --tissue_class, --tissue_type, --cancer_type.
If markers are not provided, set to False.

--species None
The species of your sample. Human or Mouse.

--tissue_class None
The tissue class of your sample. View options in CellMarker2.0.

--tissue_type None
The tissue type of your sample. View options in CellMarker2.0.

--cancer_type Normal
The cancer type of your sample. View options in CellMarker2.0.

Filter arguments

--f True
Whether to filter .h5ad file. if False, generate only HTML report.

--s 5
Sections with a median score less than s will be removed.

--n 0.7
Determine the value of min_genes to ensure that the valid cell ratio is greater than --n. min_genes is adjusted to the nearest multiple of 10. If min_genes is already divisible by 10, it remains unchanged. Otherwise, min_genes is rounded down to the nearest multiple of 10.

--min_genes None
Provide your min_genes, otherwise determined by --n.

--l 0.99

After filtering cells, determine the value of min_cells to ensure that the proportion of marker genes is greater than --l among the remaining detected markers.

--min_cells None
Provide your min_cells, otherwise determined by --l.

--mito_percent 0.1
Filter cells with mitochondrial proportion higher than --mito_percent.

Cell score arguments

--s1 -1 0
percent.mt_score of the cell.
percent_mito > --mito_percent: -1
percent_mito <= --mito_percent: 0

--s2 0.8 0 1
log10GenesPerUMI_score of the cell.
log10GenesPerUMI < 0.8: 0
log10GenesPerUMI >= 0.8: 1

--s3 0.2 0.5 0 1 2
n_genes_score of the cell.
n_genes ranking below 20th percentile: 0
between 20th and 50th percentile: 1
above 50th percentile: 2

--s4 0.2 0.5 0.8 0 1 2 3
markerDetectionRatio_score of the cell.
markerDetectionRatio ranking below 20th percentile: 0
between 20th and 50th percentile: 1
between 50th and 80th percentile: 2
above 80th percentile: 3

--s5 0.2 0.5 0.8 0 1 2 3]
markerProportion_score of the cell.
markerProportion_score ranking below 20th percentile: 0
between 20th and 50th percentile: 1
between 50th and 80th percentile: 2
above 80th percentile: 3

--s6 0.2 0.5 0.8 0 1 2 3
markerCountsRatio_score of the cell.
markerCountsRatio_score ranking below 20th percentile: 0
between 20th and 50th percentile: 1
between 50th and 80th percentile: 2
above 80th percentile: 3

--s7 -4 0
doublet_score of the cell.
doublet cells: -4
not doublet cells: 0

--s8 0.2 0.5 0 1 2
n_counts_score.
n_counts ranking below 20th percentile: 0
between 20th and 50th percentile: 1
above 50th percentile: 2

Options

--bin_value 100
Values of n_genes bin intervals applied to the HTML button: Marker Proportion.

--min_genes_list 0, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1100
used for HTML buttons: Cell Number Post Filter, Markers Proportion Post Filter, Markers Detected Post Filter.

--min_genes_list2 0, 100, 200, 300, 400, 500, 600, 700
used for HTML button: Valid Cell Post min_genes.

--min_cells_list 3, 10, 20
used for html buttons: Markers Proportion Post Filter, Markers Detected Post Filter.

--output ./
output directory.

--o1 report.html
The filename for the output of html report.

--o2 filtered.h5ad
The filename for the output of filtered .h5ad.

--j 8
The maximum number of concurrently running jobs. If set to 1, parallelism is not used. If set to -1, all CPUs are used. For n_jobs less than -1, (n_cpus + 1 + n_jobs) CPUs are used.