Demultiplex single-cell antibody repertoires with precision and paired insight.
Project description
PairPlex
Demultiplex single-cell antibody repertoires with native pairing.
Paired santibody sequences at high-throughput fr a fraction of the cost leaves you PairPlex? So were we!
PairPlex uses combinatorial barcoding and single-cell RNA-seq to obtain paired antibody sequences in a super high-throughput fashion.
In January 2025, a novel method was unveiled to massively increase the scale of single-cell sequencing by making use of a combinatorial indexing approach [1]. We took on the endeavor to adapt this approach to BCR/antibody repertoire sequencing, largely enhancing available methods to obtain natively-paired anitbody sequences at a high-throughput. In a nutshell, this method combines 10X-Genomics approach to VDJ sequencing with the throughput of bulkNGS techniques. Thanks to the use of a 5'RACE-based approach, the obtain antibody repertoire is largely unbiased. Maximal length (2x300bp) short reads-based sequencing ensure the hightest possible quality of sequencing. Following sequencing, demultiPLEXing and PAIRing of sequences must be performed. PairPlex is a Python-coded pipeline that handles these tasks from sequencing data all the way to fully annotated AIRR-compatible paired sequences tables.
Full protocol is available here: [Protocols.io][2]
The python code for PairPlex is available in the present GitHub repository: [GitHub][3]
Using this approach and PairPlex, we generated a database of XX million natively paired antibody sequences from 8 healthy donors. In addition, we also sequenced the immune loci for these donors and annotated the resulting antibody repertoires using customized donor-matching germline databases, hence providing an outstanding antibody repertoire.
This full dataset is made available here: [XXM-PairedAntibodyRepertoire] [4]
Antibody sequences will also be integrated to the Observed Antibody Space (OAS) database
Welcome to a whole new antibody dimension! Yes, you too can be PairPlex!
[1]: Li, Y., Huang, Z., Xu, L. et al. UDA-seq: universal droplet microfluidics-based combinatorial indexing for massive-scale multimodal single-cell sequencing. Nat Methods (2025). https://doi.org/10.1038/s41592-024-02586-y
[2]: https://protocols.io/blablabla
[3]: https://github.com/brineylab/pairplex
[4]: Link-to-database
Requirements and Installation
PairPlex makes extensive use of the following libraries: Installation of these should however be automatically handled (with the correct versions) by the install script
To install PairPlex, two options:
With Pypi
pip install pairplex
From this repository
git clone https://github.com/brineylab/pairplex
cd pairplex
pip install ./
Verify installation
Verifying correct installation can be done by checking the version. In the Terminal interface, use:
pairplex --version
The version number should be returned
Usage
PairPlex can be used from the CLI or from the Python API
CLI
pairplex run ...
API
pairplex(sequencing_folder='./SequencingRun/', verbose=False)
Options
Many options are available. Here's a quick overview:
Reporting bugs
Citation
If you are using Pairplex or the dataset generated of paired antibody sequences, please cite:
Large-scale antibody repertoire leaves you PairPlex
some awesome people at the Briney lab
soon-to-be-published
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