Pipeline Execution

Once all the configuration dependencies are met and paramaters are set in the config.yaml, sc-VirusScan can be initiated as described below:

1. Activate the conda environment: conda activate sc-VirusScan

2. Once conda environment is activated, trigger the pipeline using following command:

snakemake --cores 16 --configfile config.yaml --latency-wait 60 --profile <Slurm_Profile_Name>

–cores: Cores to be specified for the pipeline (Minimum: 16)

–configfile: Path to the config.yaml file

–profile: If slurm profile available, specify the slurm profile name

Pipeline Outputs

On successfully completion of sc-VirusScan, following output file are generated in the respective directories as representated below.

├── results
│    ├── kraken2                                   #Kraken Classification Reports
│    │    ├── Sample1.kraken
│    │    └── Sample1.report.txt
│    │
│    ├── cellranger                                #CellRanger scRNAseq Analysis Intermediate Files
│    │  └── Sample1
│    │     ├── filtered_feature_bc_matrix
│    │     ├── raw_feature_bc_matrix
│    │     ├── possorted_genome_bam
│    │     ├── possorted_genome_bam.bai
│    │     ├── filtered_feature_bc_matrix.h5
│    │     └── raw_feature_bc_matrix.h5
│    │
│    ├── count_matrix                               #Final Count matrix result
│    │  └── Sample1/
│    │     └── count_matrix.tsv
│    │
│    └── kraken_reports                             #QC Reports and Plots based on Kraken2 Reports
│       ├── Familywise_tax_readcounts.tsv
│       ├── Specieswise_tax_readcounts.tsv
│       ├── Clustermap_Familywise_log10.png
│       └── Clustermap_Specieswise_log10.png
└── logs

The users can use the count_matrix.tsv file from the results directory along with the Cellranger barcodes in the sample wise directories under cellranger directory for further downstream single cell analysis using Seurat and ScanPy.