Demuxalot

Demuxalot is a genotype demultiplexing software that requires reference genotypes to be available for each individual in the pool. Therefore, if you don’t have reference genotypes, you may want to demultiplex with one of the softwares that do not require reference genotype data (Freemuxlet, scSplit, Souporcell or Vireo)

Data

This is the data that you will need to have prepare to run Demuxalot:

Required

• Reference SNP genotypes for each individual ($VCF)

  • Filter for common SNPs (> 5% minor allele frequency) and SNPs overlapping genes

• Barcode file ($BARCODES)

• Bam file ($BAM)

  • Aligned single cell reads

• Output directory ($DEMUXALOT_OUTDIR)

• A text file with the individual ids ($INDS)

  • File containing the individual ids (separated by line) as they appear in the vcf file

  • For example, this is the individual file for our example dataset

Run Demuxalot

Example Variable Settings

Below is an example of the variables that we can set up to be used in the command below. These are files provided as a test dataset available in the Data Preparation Documentation Please replace /path/to with the full path to your data directory.

VCF=/path/to/TestData4PipelineFull/test_dataset.vcf
BARCODES=/path/to/TestData4PipelineFull/test_dataset/outs/filtered_gene_bc_matrices/Homo_sapiens_GRCh38p10/barcodes.tsv
BAM=/path/to/test_dataset/possorted_genome_bam.bam
DEMUXALOT_OUTDIR=/path/to/output/demuxalot
INDS=/path/to/TestData4PipelineFull/donor_list.txt

Demuxalot can be run with refinement if desired - this means that there is another step that is run to refine the genotypes from the data which makes the results slightly more accurate. You can choose to run Demuxalot with or without refinement:

Demultiplex with Demuxalot

⏱️ Expected Resource Usage

~2.5h using a total of 81Gb memory when using 32 threads for the full Test Dataset which contains ~20,982 droplets of 13 multiplexed donors,

With RefinementWithout Refinement

This will run the first phase of Demuxalot as well as the subsequent refinement:

singularity exec Demuxafy.sif Demuxalot.py \
        -b $BARCODES \
        -a $BAM \
        -n $INDS \
        -v $VCF \
        -o $DEMUXALOT_OUTDIR \
        -r True

HELP! It says my file/directory doesn’t exist!

If you receive an error indicating that a file or directory doesn’t exist but you are sure that it does, this is likely an issue arising from Singularity. This is easy to fix. The issue and solution are explained in detail in the Notes About Singularity Images

If Demuxalot is successful, you will have these new files in your $DEMUXALOT_OUTDIR:

/path/to/output/demuxalot
├── assignments_refined.tsv.gz
├── assignments.tsv.gz
├── likelihoods_refined.tsv.gz
├── likelihoods.tsv.gz
├── posterior_probabilities_refined.tsv.gz
└── posterior_probabilities.tsv.gz

Additional details about outputs are available below in the Demuxalot Results and Interpretation.

Demuxalot Summary

We have provided a script that will summarize the number of droplets classified as doublets, ambiguous and assigned to each donor by Demuxalot and write it to the $DEMUXALOT_OUTDIR. You can run this to get a fast and easy summary of your results by providing the path to your result file:

With RefinementWithout Refinement

singularity exec Demuxafy.sif bash demuxalot_summary.sh $DEMUXALOT_OUTDIR/assignments_refined.tsv.gz

which will return:

Classification	Assignment N
113_113	1334
349_350	1458
352_353	1607
39_39	1297
40_40	1078
41_41	1127
42_42	1419
43_43	1553
465_466	1094
596_597	1255
597_598	1517
632_633	868
633_634	960
660_661	1362
doublet	3053

or you can write it straight to a file:

singularity exec Demuxafy.sif bash Demuxalot_summary.sh $DEMUXALOT_OUTDIR/assignments_refined.tsv.gz > $DEMUXALOT_OUTDIR/demuxalot_summary.tsv

Note

To check if these numbers are consistent with the expected doublet rate in your dataset, you can use our Doublet Estimation Calculator.

Demuxalot Results and Interpretation

After running the Demuxalot steps and summarizing the results, you will have a number of files from some of the intermediary steps. These are the files that most users will find the most informative:

• assignments.tsv.gz (and assignments_refined.tsv.gz if you indicated -r True)

  • The droplet assignment for each barcode:

    BARCODE	0
    AAACCTGAGATAGCAT-1	41_41
    AAACCTGAGCAGCGTA-1	465_466
    AAACCTGAGCGATGAC-1	113_113
    AAACCTGAGCGTAGTG-1	349_350
    AAACCTGAGGAGTTTA-1	632_633
    AAACCTGAGGCTCATT-1	39_39
    …	…

• likelihoods_refined.tsv.gz or likelihoods.tsv.gz:

  • The likelihood probabilities for each donor and doublet combination for each droplet

• posterior_probabilities_refined.tsv.gz or posterior_probabilities_refined.tsv.gz

  • The posterior probabilities for each donor or doublet combination for each droplet

Merging Results with Other Software Results

We have provided a script that will help merge and summarize the results from multiple softwares together. See Combine Results.

Citation

If you used the Demuxafy platform for analysis, please reference our preprint as well as Demuxalot.