SComatic-nf

Pipeline to datect somatic variants from single-cell sequencing data

Description

Pipeline for detecting somatic single-nucleotide mutations in high-throughput single-cell genomics and transcriptomics data sets, such as single-cell RNA-seq and single-cell ATAC-se (using SComatic) and de novo extraction of mutational signatures (using SigProfilerExtractor).

Pipeline runs in following steps:
  Step1-4 : SComatic steps
  annovar : annotated all variants using annovar
  preprocessing : to create input for SigProfilerExtractor from SComatic output
  Step5_sigprofiler : de-novo extraction of mutational signatures using SigProfilerExtractor

Dependencies

1. This pipeline is based on nextflow. As we have several nextflow pipelines, we have centralized the common information in the IARC-nf repository. Please read it carefully as it contains essential information for the installation, basic usage and configuration of nextflow and our pipelines.
2. SComatic
3. annovar
4. SigProfilerExtractor

You can avoid installing all the external software by only installing Docker. See the IARC-nf repository for more information.

Input

Type	Description
--bam_folder	Folder containing BAM files (*bai must be available in the same folder).
--meta	Metadata file mapping cell barcodes to cell type.

Parameters

• Mandatory

Name	Example value	Description
--scomat_path	/Users/lipika/SComatic	Scomatic installation folder path
--ref	ref.fa	genome reference files (with index)
--annovar_path	/Users/lipika/annovar	path to annovar
--hdb	/Users/lipika/humandb	path to human database for annotation (refGene,cytoBand,exac03,avsnp147,dbnsfp30a,gnomad_genome- required)
--hg_build	GRCh38	genome build

• Optional

Name	Default value	Description
--cpu	2	Number of CPUs
--mem	20	memory
--output_folder	SComatic-nf-results	Output folder
--nTrim	5	Number of bases trimmed by setting the base quality to 0 at the beginning and end of each read
--maxNM	5	Maximum number of mismatches permitted to consider reads for analysis
--maxNH	1	Maximum number of alignment hits permitted to consider reads for analysis
--chrom	all	Chromosome to be analysed
--minbq	30	Minimum base quality permited for the base counts
--nprocs	1	Number of processes
--pon	30	Panel of normals (PoN) file to be used to remove germline polymorphisms and recurrent artefacts
--min_signatures	1	Minimum number of Mutational signatures
--max_signatures	10	Maximum number of Mutational signatures

• Flags

Flags are special parameters without value.

Name	Description
--help	Display help

Usage

annovar database files for hg38 could be downloaded using the command below (example shown for avsnp147)

perl path/to/annovar/annotate_variation.pl -buildver hg38 -downdb -webfrom annovar avsnp147 humandb/

Install reference genome to be used in SigProfilerExtractor using python

$ python
from SigProfilerMatrixGenerator import install as genInstall
genInstall.install('GRCh38')

To use SComatic on your bamFile.bam, having metadata.tsv file mapping cell barcodes to cell type and reference genome ref.fa used in alignment fro hg38 genome build, use this command

nextflow run iarcbioinfo/SComatic-nf --bam_folder bamFile.bam --meta metadata.tsv --ref ref.fa --scomat_path path/to/Scomatfolder --annovar_path path/to/annovar --hdb path/to/humandb --hg_build GRCh38

Output

Type	Description
SplitBamCellTypes/sample.*.bam	Folder containing cell-type-specific BAM files (step1 output)
Step2_BaseCellCounts/sample.*.tsv	Folder containing base count information for each cell type and for every position in the genome (step2 output)
Step3_BaseCellCountsMerged/sample.BaseCellCounts.AllCellTypes.tsv	Folder containing merged base count file of all cell types. (step3 output)
Step4_VariantCalling/sample.calling.step*.tsv (*=1,2)	Folder containing two files files (1*.tsv: SNV called after applying filters for removing technical artefacts, 2*.tsv: Further filtered for RNA editing and PoN). (step4 output)
sigprofiler-input/sample_*.bam	Folder containing input files for SigProfilerExtractor.
sigprofiler-results/*	Folder containing result files and folders from SigProfilerExtractor.

Contributions

Name	Email	Description
Lipika Kalson		Developer
Nicolas Alcala	alcalan@iarc.who.int	Developer to contact for support

References

Muyas, F., Sauer, C.M., Valle-Inclán, J.E. et al. De novo detection of somatic mutations in high-throughput single-cell profiling data sets. Nat Biotechnol (2023). https://doi.org/10.1038/s41587-023-01863-z