$ pyscenic ctx --help
usage: pyscenic ctx [-h] [-o OUTPUT] [-n] [--chunk_size CHUNK_SIZE]
[--mode {custom_multiprocessing,dask_multiprocessing,dask_cluster}]
[-a] [-t] [--rank_threshold RANK_THRESHOLD]
[--auc_threshold AUC_THRESHOLD]
[--nes_threshold NES_THRESHOLD]
[--min_orthologous_identity MIN_ORTHOLOGOUS_IDENTITY]
[--max_similarity_fdr MAX_SIMILARITY_FDR]
--annotations_fname ANNOTATIONS_FNAME
[--num_workers NUM_WORKERS]
[--client_or_address CLIENT_OR_ADDRESS]
[--thresholds THRESHOLDS [THRESHOLDS ...]]
[--top_n_targets TOP_N_TARGETS [TOP_N_TARGETS ...]]
[--top_n_regulators TOP_N_REGULATORS [TOP_N_REGULATORS ...]]
[--min_genes MIN_GENES]
[--expression_mtx_fname EXPRESSION_MTX_FNAME]
[--mask_dropouts] [--cell_id_attribute CELL_ID_ATTRIBUTE]
[--gene_attribute GENE_ATTRIBUTE] [--sparse]
module_fname database_fname [database_fname ...]
positional arguments:
module_fname The name of the file that contains the signature or
the co-expression modules. The following formats are
supported: CSV or TSV (adjacencies), YAML, GMT and DAT
(modules)
database_fname The name(s) of the regulatory feature databases. Two
file formats are supported: feather or db (legacy).
optional arguments:
-h, --help show this help message and exit
-o OUTPUT, --output OUTPUT
Output file/stream, i.e. a table of enriched motifs
and target genes (csv, tsv) or collection of regulons
(yaml, gmt, dat, json).
-n, --no_pruning Do not perform pruning, i.e. find enriched motifs.
--chunk_size CHUNK_SIZE
The size of the module chunks assigned to a node in
the dask graph (default: 100).
--mode {custom_multiprocessing,dask_multiprocessing,dask_cluster}
The mode to be used for computing (default:
dask_multiprocessing).
-a, --all_modules Included positive and negative regulons in the
analysis (default: no, i.e. only positive).
-t, --transpose Transpose the expression matrix (rows=genes x
columns=cells).
motif enrichment arguments:
--rank_threshold RANK_THRESHOLD
The rank threshold used for deriving the target genes
of an enriched motif (default: 5000).
--auc_threshold AUC_THRESHOLD
The threshold used for calculating the AUC of a
feature as fraction of ranked genes (default: 0.05).
--nes_threshold NES_THRESHOLD
The Normalized Enrichment Score (NES) threshold for
finding enriched features (default: 3.0).
motif annotation arguments:
--min_orthologous_identity MIN_ORTHOLOGOUS_IDENTITY
Minimum orthologous identity to use when annotating
enriched motifs (default: 0.0).
--max_similarity_fdr MAX_SIMILARITY_FDR
Maximum FDR in motif similarity to use when annotating
enriched motifs (default: 0.001).
--annotations_fname ANNOTATIONS_FNAME
The name of the file that contains the motif
annotations to use.
computation arguments:
--num_workers NUM_WORKERS
The number of workers to use. Only valid if using
dask_multiprocessing, custom_multiprocessing or local
as mode. (default: 32).
--client_or_address CLIENT_OR_ADDRESS
The client or the IP address of the dask scheduler to
use. (Only required of dask_cluster is selected as
mode)
module generation arguments:
--thresholds THRESHOLDS [THRESHOLDS ...]
The first method to create the TF-modules based on the
best targets for each transcription factor (default:
0.75 0.90).
--top_n_targets TOP_N_TARGETS [TOP_N_TARGETS ...]
The second method is to select the top targets for a
given TF. (default: 50)
--top_n_regulators TOP_N_REGULATORS [TOP_N_REGULATORS ...]
The alternative way to create the TF-modules is to
select the best regulators for each gene. (default: 5
10 50)
--min_genes MIN_GENES
The minimum number of genes in a module (default: 20).
--expression_mtx_fname EXPRESSION_MTX_FNAME
The name of the file that contains the expression
matrix for the single cell experiment. Two file
formats are supported: csv (rows=cells x
columns=genes) or loom (rows=genes x columns=cells).
(Only required if modules need to be generated)
--mask_dropouts If modules need to be generated, this controls whether
cell dropouts (cells in which expression of either TF
or target gene is 0) are masked when calculating the
correlation between a TF-target pair. This affects
which target genes are included in the initial
modules, and the final pruned regulon (by default only
positive regulons are kept (see --all_modules
option)). The default value in pySCENIC 0.9.16 and
previous versions was to mask dropouts when
calculating the correlation; however, all cells are
now kept by default, to match the R version.
loom file arguments:
--cell_id_attribute CELL_ID_ATTRIBUTE
The name of the column attribute that specifies the
identifiers of the cells in the loom file.
--gene_attribute GENE_ATTRIBUTE
