nf-core/scdownstream
A single cell transcriptomics pipeline for QC, integration and making the data presentable
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.
string^\S+\.csv$The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.
stringSave intermediate files to the output directory
booleanEmail address for completion summary.
string^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$MultiQC report title. Printed as page header, used for filename if not otherwise specified.
stringOptions for converting the input data to the unified format.
Unify gene symbols to the latest version of the Ensembl database
booleanMethod to aggregate gene expression values for non-unique genes
stringForce keeping certain columns in the merged AnnData object, even if they are not present in all samples
string^([a-zA-Z0-9_]*(,[a-zA-Z0-9_]*)*)?$Aggregate isoforms of the same gene. If set to true, genes like ‘SOD2.1’ will be renamed to ‘SOD2’ before duplicate_var_resolution is applied. All numeric suffixes following a dot will be removed.
booleanOptions for quality control of the input data.
Optional file containing a list of mitochondrial gene symbols (one per line). If provided, it overrides the default ‘mt-’ prefix heuristic.
stringSpecify the tool to use for ambient RNA correction. If ‘none’ is selected, no ambient RNA correction will be performed. If you want to use ambient RNA correction only for a subset of datasets, you can use the ‘ambient_correction’ column in the sample sheet. By default, the ambient-corrected counts will NOT be used for integration, but only stored as an additional layer in the final AnnData object because of the findings in this publication. If you want to use the ambient-corrected counts for integration, set ambient_corrected_integration to true in the sample sheet.
stringWhether to use the ambient-corrected counts for integration. Can be overridden by the ambient_corrected_integration in the sample sheet.
booleanSpecify the tools to use for doublet detection. Setting to ‘none’ will skip this step
stringscrublet^(none|((solo|scrublet|doubletdetection|scds)?,?)*[^,]+$)Number of tools that need to agree on a doublet for it to be called as such
integer1Number of epochs to train the CellBender model
integer150Options 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
stringscvi^((scvi|scanvi|harmony|bbknn|combat|seurat|scimilarity)(,(scvi|scanvi|harmony|bbknn|combat|seurat|scimilarity))*)?$Number of highly variable genes to use for integration. If set to 0, the number of highly variable genes will be automatically determined. If set to a negative number, all genes will be used.
integerPath to a pre-trained scVI model, only relevant if scVI is selected in integration_methods. If provided, the model will be used for integration. Otherwise, a new model will be trained.
string^\S+\.pt$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.
string^\S+\.pt$Path to a pre-trained scimilarity model, only relevant if scimilarity is selected in integration_methods. If provided, the model will be used for integration. Otherwise, a new model will be trained.
stringhttps://zenodo.org/records/10685499/files/model_v1.1.tar.gzIf you already produced an integrated AnnData object with this pipeline and want to add new data to it, you can specify the path to the base AnnData object and some information about it here. This will allow you to project the new data onto the existing integrated object.
If you want to project new data onto an already integrated object, specify the path to the base AnnData object here
string^\S+\.h5ad$The column in the base AnnData object that contains the label (e.g. cell type) information.
stringlabelThe 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.
string^((scvi|scanvi|harmony|bbknn|combat|seurat)(,(scvi|scanvi|harmony|bbknn|combat|seurat))*)?$Options for clustering the integrated data.
Specify the resolutions for clustering
string0.5,1.0^\d+(\.\d+)?(,\d+(\.\d+)?)*$Create a UMAP and a clustering for each unique value in the label column (and for each integration method)
booleanCreate a global UMAP and clustering (for each integration method)
booleantrueOptions for various tools used in the pipeline.
Specify the models to use for the celltypist cell type annotation
string^([a-zA-Z0-9_]*(,[a-zA-Z0-9_]*)*)?$Path to comma-separated file containing information about the celldex references to use for the singleR cell type annotation.
string^\S+\.csv$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.
integer1Use GPU acceleration for tasks that support it
booleanOptions for selecting which tools should be used for certain tasks
Only run the preprocessing steps, skip the integration and clustering steps
booleanSkip the LIANA step. For large datasets, the pipeline might fail due to high memory usage in this step. Use this option to skip it.
booleanSkip 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.
booleanPerform pseudobulking
booleanPrepare the output for visualisation in cellxgene
booleanOptions for the scVI and scANVI integration methods
Number of latent dimensions for scVI/scANVI
integer30Number of hidden units in the neural network for scVI/scANVI
integer128Number of layers in the neural network for scVI/scANVI
integer2Dispersion parameter for scVI/scANVI
stringGene likelihood for scVI/scANVI
stringMaximum number of epochs for training scVI/scANVI. If not set, a heuristic provided by scVI/scANVI will be used.
integerCategorical covariates for scVI/scANVI
stringContinuous covariates for scVI/scANVI
stringOptions for pseudobulking
Group by labels for pseudobulking. If you want to use multiple labels, separate them with a comma.
stringbatchMinimum number of cells for pseudobulking
integer5Parameters used to describe centralised config profiles. These should not be edited.
Git commit id for Institutional configs.
stringmasterBase directory for Institutional configs.
stringhttps://raw.githubusercontent.com/nf-core/configs/masterInstitutional config name.
stringInstitutional config description.
stringInstitutional config contact information.
stringInstitutional config URL link.
stringLess common options for the pipeline, typically set in a config file.
Display version and exit.
booleanMethod used to save pipeline results to output directory.
stringEmail address for completion summary, only when pipeline fails.
string^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$Send plain-text email instead of HTML.
booleanFile size limit when attaching MultiQC reports to summary emails.
string25.MB^\d+(\.\d+)?\.?\s*(K|M|G|T)?B$Do not use coloured log outputs.
booleanIncoming hook URL for messaging service
stringCustom config file to supply to MultiQC.
stringCustom logo file to supply to MultiQC. File name must also be set in the MultiQC config file
stringCustom MultiQC yaml file containing HTML including a methods description.
stringBoolean whether to validate parameters against the schema at runtime
booleantrueBase URL or local path to location of pipeline test dataset files
stringhttps://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.
string