nf-core/hadge (hashing deconvolution combined with genotype information) is a bioinformatics pipeline that combines 11 methods to perform both hashing- and genotype-based deconvolution on single cell multiplexing data. It takes a samplesheet with count matrices, BAM and VCF files as input, performs deconvolution with every method, joins all results and finally recovers previously discarded cells by combining the best performing methods (donor matching).
- Untar matrices
- Extract hto names from matrix
- Perform genetic-based deconvolution
- Get single cell genotype
cellSNP vireodemuxletfreemuxletsouporcell
- Get single cell genotype
- summarize assignments and classifications
- Perform hashing-based deconvolution
- summarize assignments and classifications
- Join all results
- Donor match
- Find informative variants
- Create AnnData and Mudata objects
MultiQC
Note
If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data. The profile test is used to test hadge's rescue mode, but you can also test the other modes with the profiles test_genetic, test_hashing and test_donor_match.
First, prepare a samplesheet with your input data that looks as follows:
samplesheet.csv:
sample,rna_matrix,hto_matrix,bam,vcf,n_samples,barcodes
id1,rna.tar.gz,hto.tar.gz,chr21.bam,donor_genotype_chr21.vcf,2,barcodes.tsv
id2,rna.tar.gz,hto.tar.gz,chr21.bam,donor_genotype_chr21.vcf,2,barcodes.tsv
id3,rna.tar.gz,hto.tar.gz,chr21.bam,donor_genotype_chr21.vcf,2,barcodes.tsvEach row contains data from a single-cell multiplexing experiment. The RNA-seq (rna_matrix) and hashing (hto_matrix) count matrices are provided in a 10x Genomics format and compressed as .tar.gz.
Genetic deconvolution requires both the alignment file (bam) and a list of common SNPs (vcf). Users must specify the number of multiplexed donors (n_samples) and identify the target cells for deconvolution (barcodes).
Now, you can run the pipeline using:
nextflow run nf-core/hadge \
-profile <docker/singularity/.../institute> \
--input samplesheet.csv \
--outdir <OUTDIR> \
--mode rescue \
--hash_tools htodemux,hasheddrops,multiseq,gmm-demux,bff,hashsolo \
--genetic_tools demuxlet,freemuxlet,vireo,souporcell \
--fasta <FASTADIR>Warning
Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.
For more details and further functionality, please refer to the usage documentation and the parameter documentation.
To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.
nf-core/hadge was originally written by Fabiola Curion (@bio-la), Xichen Wu (@wxicu), Lukas Heumos (@zethson) and Mariana Gonzales Andre (@mari-ga).
We thank the following people for their extensive assistance in the development of this pipeline:
If you would like to contribute to this pipeline, please see the contributing guidelines.
For further information or help, don't hesitate to get in touch on the Slack #hadge channel (you can join with this invite).
An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.
You can cite the nf-core publication as follows:
The nf-core framework for community-curated bioinformatics pipelines.
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.
Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
