🚀 Quickstart

Activate the snakemake environment

conda activate snakemake

Call the pipeline with -n for a dry run and -q for reduced output. Here’s the command for running preprocessing, integration and metrics

bash run_example.sh preprocessing_all integration_all metrics_all -nq

Job stats:
job                                    count
-----------------------------------  -------
integration_all                            1
integration_barplot_per_dataset            3
integration_benchmark_per_dataset          1
integration_compute_umap                   6
integration_plot_umap                      6
integration_postprocess                    6
integration_prepare                        1
integration_run_method                     3
preprocessing_assemble                     1
preprocessing_highly_variable_genes        1
preprocessing_normalize                    1
preprocessing_pca                          1
total                                     31

Reasons:
    (check individual jobs above for details)
    input files updated by another job:
        integration_all, integration_barplot_per_dataset, integration_benchmark_per_dataset, integration_compute_umap, integration_plot_umap, integration_postprocess, integration_prepare, integration_run_method, preprocessing_assemble, preprocessing_highly_variable_genes, preprocessing_pca                                                                                             
    missing output files:
        integration_benchmark_per_dataset, integration_compute_umap, integration_postprocess, integration_prepare, integration_run_method, preprocessing_assemble, preprocessing_highly_variable_genes, preprocessing_normalize, preprocessing_pca

This was a dry-run (flag -n). The order of jobs does not reflect the order of execution.

If the dryrun was successful, you can let Snakemake compute the different steps of the workflow with e.g. 10 cores:

bash run_example.sh preprocessing_all integration_all metrics_all -c 10

You have now successfully called the example pipeline! 🎉
Read on to learn how to configure your own workflow.