Lianapy

Performs LIANA integration based as described in https://github.com/saezlab/liana-py

Info

ID: lianapy
Namespace: interpret

Example commands

You can run the pipeline using nextflow run.

View help

You can use --help as a parameter to get an overview of the possible parameters.

nextflow run openpipelines-bio/openpipeline \
  -r 1.0.2 -latest \
  -main-script target/nextflow/interpret/lianapy/main.nf \
  --help

Run command

Example of params.yaml
# Arguments
input: # please fill in - example: "path/to/file"
# output: "$id.$key.output.output"
output_compression: "gzip"
modality: "rna"
# layer: "foo"
groupby: "bulk_labels"
resource_name: "consensus"
gene_symbol: "gene_symbol"
expr_prop: 0.1
min_cells: 5
aggregate_method: "rra"
return_all_lrs: false
n_perms: 100

# Nextflow input-output arguments
publish_dir: # please fill in - example: "output/"
# param_list: "my_params.yaml"
nextflow run openpipelines-bio/openpipeline \
  -r 1.0.2 -latest \
  -profile docker \
  -main-script target/nextflow/interpret/lianapy/main.nf \
  -params-file params.yaml
Note

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

Argument group

Arguments

Name Description Attributes
--input Input h5mu file file, required
--output Output h5mu file. file, required
--output_compression string, default: "gzip"
--modality string, default: "rna"
--layer Layer in anndata.AnnData.layers to use. If None, use mudata.mod[modality].X. string
--groupby The key of the observations grouping to consider. string, default: "bulk_labels"
--resource_name Name of the resource to be loaded and use for ligand-receptor inference. string, default: "consensus"
--gene_symbol Column name in var DataFrame in which gene symbol are stored. string, default: "gene_symbol"
--expr_prop Minimum expression proportion for the ligands/receptors (and their subunits) in the corresponding cell identities. Set to ‘0’, to return unfiltered results. double, default: 0.1
--min_cells Minimum cells per cell identity (‘groupby’) to be considered for downstream analysis. integer, default: 5
--aggregate_method Method aggregation approach, one of [‘mean’, ‘rra’], where ‘mean’ represents the mean rank, while ‘rra’ is the RobustRankAggregate (Kolde et al., 2014) of the interactions. string, default: "rra"
--return_all_lrs Bool whether to return all LRs, or only those that surpass the ‘expr_prop’ threshold. Those interactions that do not pass the ‘expr_prop’ threshold will be assigned to the worst score of the ones that do. ‘False’ by default. boolean, default: FALSE
--n_perms Number of permutations for the permutation test. Note that this is relevant only for permutation-based methods - e.g. ’CellPhoneDB integer, default: 100

Authors

  • Mauro Saporita (author)

  • Povilas Gibas (author)