Define where the pipeline should find input data and save output data.

Path to comma-separated file containing information about the samples in the experiment.

type: string
pattern: ^\S+\.csv$

The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.

required
type: string

Save intermediate files to the output directory

type: boolean

Email address for completion summary.

type: string
pattern: ^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$

MultiQC report title. Printed as page header, used for filename if not otherwise specified.

type: string

Options for converting the input data to the unified format.

Unify gene symbols to the latest version of the Ensembl database

type: boolean

Method to aggregate gene expression values for non-unique genes

type: string

Force keeping certain columns in the merged AnnData object, even if they are not present in all samples

type: string
pattern: ^([a-zA-Z0-9_]*(,[a-zA-Z0-9_]*)*)?$

Aggregate isoforms of the same gene. If set to true, genes like ‘SOD2.1’ will be renamed to ‘SOD2’ before duplicate_var_resolution is applied. All numeric suffixes following a dot will be removed.

type: boolean

Options for quality control of the input data.

Specify the tool to use for ambient RNA removal

type: string

Specify the tools to use for doublet detection. Setting to ‘none’ will skip this step

type: string
default: scrublet
pattern: ^(none|((solo|scrublet|doubletdetection|scds)?,?)*[^,]+$)

Number of tools that need to agree on a doublet for it to be called as such

type: integer
default: 1

Number of epochs to train the CellBender model

type: integer
default: 150

Options for integration of the input data. For configuration of the scVI/scANVI models, see the scVI_options section.

Specify the tool to use for integration

type: string
default: scvi
pattern: ^((scvi|scanvi|harmony|bbknn|combat|seurat|scimilarity)(,(scvi|scanvi|harmony|bbknn|combat|seurat|scimilarity))*)?$

Number of highly variable genes to use for integration. If set to 0, the number of highly variable genes will be automatically determined. If set to a negative number, all genes will be used.

type: integer

Path to a pre-trained scVI model, only relevant if scVI is selected in integration_methods. If provided, the model will be used for integration. Otherwise, a new model will be trained.

type: string
pattern: ^\S+\.pt$

Path to a pre-trained scANVI model, only relevant if scANVI is selected in integration_methods. If provided, the model will be used for integration. Otherwise, a new model will be trained.

type: string
pattern: ^\S+\.pt$

Path to a pre-trained scimilarity model, only relevant if scimilarity is selected in integration_methods. If provided, the model will be used for integration. Otherwise, a new model will be trained.

type: string
default: https://zenodo.org/records/10685499/files/model_v1.1.tar.gz

If you already produced an integrated AnnData object with this pipeline and want to add new data to it, you can specify the path to the base AnnData object and some information about it here. This will allow you to project the new data onto the existing integrated object.

If you want to project new data onto an already integrated object, specify the path to the base AnnData object here

type: string
pattern: ^\S+\.h5ad$

The column in the base AnnData object that contains the label (e.g. cell type) information.

type: string
default: label

The keys in the obsm of the base AnnData object that contain the embeddings (without leading X_). Required if input is not provided - otherwise it is ignored.

type: string
pattern: ^((scvi|scanvi|harmony|bbknn|combat|seurat)(,(scvi|scanvi|harmony|bbknn|combat|seurat))*)?$

Options for clustering the integrated data.

Specify the resolutions for clustering

type: string
default: 0.5,1.0
pattern: ^\d+(\.\d+)?(,\d+(\.\d+)?)*$

Create a UMAP and a clustering for each unique value in the label column (and for each integration method)

type: boolean

Create a global UMAP and clustering (for each integration method)

type: boolean
default: true

Options for various tools used in the pipeline.

Specify the models to use for the celltypist cell type annotation

type: string
pattern: ^([a-zA-Z0-9_]*(,[a-zA-Z0-9_]*)*)?$

Path to comma-separated file containing information about the celldex references to use for the singleR cell type annotation.

type: string
pattern: ^\S+\.csv$

Options for resource allocation and CPU usage.

Scale the memory requirements for each process by this factor. Should be increased if you have a large number of cells.

type: integer
default: 1

Use GPU acceleration for tasks that support it

hidden
type: boolean

Options for selecting which tools should be used for certain tasks

Only run the preprocessing steps, skip the integration and clustering steps

type: boolean

Skip the LIANA step. For large datasets, the pipeline might fail due to high memory usage in this step. Use this option to skip it.

type: boolean

Skip the rank_genes_groups step. For large datasets, the pipeline might fail due to high memory usage in this step. Use this option to skip it.

type: boolean

Perform pseudobulking

type: boolean

Prepare the output for visualisation in cellxgene

type: boolean

Options for the scVI and scANVI integration methods

Number of latent dimensions for scVI/scANVI

type: integer
default: 30

Number of hidden units in the neural network for scVI/scANVI

type: integer
default: 128

Number of layers in the neural network for scVI/scANVI

type: integer
default: 2

Dispersion parameter for scVI/scANVI

type: string

Gene likelihood for scVI/scANVI

type: string

Maximum number of epochs for training scVI/scANVI. If not set, a heuristic provided by scVI/scANVI will be used.

type: integer

Categorical covariates for scVI/scANVI

type: string

Continuous covariates for scVI/scANVI

type: string

Options for pseudobulking

Group by labels for pseudobulking. If you want to use multiple labels, separate them with a comma.

type: string
default: batch

Minimum number of cells for pseudobulking

type: integer
default: 5

Parameters used to describe centralised config profiles. These should not be edited.

Git commit id for Institutional configs.

hidden
type: string
default: master

Base directory for Institutional configs.

hidden
type: string
default: https://raw.githubusercontent.com/nf-core/configs/master

Institutional config name.

hidden
type: string

Institutional config description.

hidden
type: string

Institutional config contact information.

hidden
type: string

Institutional config URL link.

hidden
type: string

Less common options for the pipeline, typically set in a config file.

Display version and exit.

hidden
type: boolean

Method used to save pipeline results to output directory.

hidden
type: string

Email address for completion summary, only when pipeline fails.

hidden
type: string
pattern: ^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$

Send plain-text email instead of HTML.

hidden
type: boolean

File size limit when attaching MultiQC reports to summary emails.

hidden
type: string
default: 25.MB
pattern: ^\d+(\.\d+)?\.?\s*(K|M|G|T)?B$

Do not use coloured log outputs.

hidden
type: boolean

Incoming hook URL for messaging service

hidden
type: string

Custom config file to supply to MultiQC.

hidden
type: string

Custom logo file to supply to MultiQC. File name must also be set in the MultiQC config file

hidden
type: string

Custom MultiQC yaml file containing HTML including a methods description.

type: string

Boolean whether to validate parameters against the schema at runtime

hidden
type: boolean
default: true

Base URL or local path to location of pipeline test dataset files

hidden
type: string
default: https://raw.githubusercontent.com/nf-core/test-datasets/be82517a080e70628dce694c61eb91821850aea9/

Suffix to add to the trace report filename. Default is the date and time in the format yyyy-MM-dd_HH-mm-ss.

hidden
type: string