SampleQC

The Snakemake pipeline integrates NTSM and VerifyBamID to verify sample identity and detect potential contamination in sequencing data.

Requirements

• Snakemake 7+
• Singularity (or Apptainer) for running the ntsm Docker image
• Python libraries (for plotting step):
  • pandas
  • numpy
  • seaborn
  • matplotlib

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Input Data

Manifest (manifest.tab)

The manifest must include:

• ID — Unique identifier for each dataset
• FOFN — File-of-filenames (list of FASTQ/FASTA files)
• TYPE - Sequencing platform or data type Choose one of the following:
  • PacBio
  • ONT
  • Illumina

Example:

ID	FOFN	TYPE
SampleA	fofn/SampleA.fofn	PacBio
SampleB	fofn/SampleB.fofn	ONT
SampleC	fofn/SampleC.fofn	Illumina

Config (config.yaml)

Important keys:

• MANIFEST: Path to the manifest file
• REF_SITE: Reference sites fasta (default: db_source/human_sites_n10.fa, relative to the Snakefile directory)
• EXTERNAL_COUNTS_DIR: Directory containing external count files (optional)
• COUNT_FILE_EXP: File extension for the external count files(default: count)

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Running the Pipeline

1. Edit config.yaml and manifest.tab to reflect your datasets.
2. Run Snakemake:

   ln -s /net/eichler/vol28/software/pipelines/ntsm_smk/runcluster .
   ./runcluster 30

References

• NTSM: https://github.com/JustinChu/ntsm
• VerifyBamID: https://github.com/Griffan/VerifyBamID.git