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.