Which is the best pipeline for demultiplexing sample hashing in single-cell sequencing?

Question

[dugong]

Which is the best pipeline for demultiplexing sample hashing in single-cell sequencing (to assign cells to samples)?

Antibody- or lipid-conjugated poly-A-RNA barcodes allow pooling many samples in a single microfluidic single-cell library preparation run, where samples can later be digitally demultiplexed.

Despite rapid developments in single cell sequencing, sample-specific batch effects, detection of cell multiplets, and experimental costs remain outstanding challenges. Here, we introduce Cell Hashing, where oligo-tagged antibodies against ubiquitously expressed surface proteins uniquely label cells from distinct samples, which can be subsequently pooled. By sequencing these tags alongside the cellular transcriptome, we can assign each cell to its original sample, robustly identify cross-sample multiplets, and “super-load” commercial droplet-based systems for significant cost reduction. source

Pipelines I know of:

1. deMULTIplex
2. CellRanger’s Feature Barcode Analysis
3. CITE-Seq Count
4. Seurat
5. DemuxEM
6. Solo
7. GMM-Demux

I did not compare how well they work, but if someone did, your insight would be appreciated. I guess accuracy would be the most important (e.g. using human + mouse cell) then ease of use.

Thank you!