Donor multiplexing is a powerful strategy to increase scale, lower the costs, and reduce batch effects in single-cell RNA sequencing (scRNAseq), but clear guidelines for experimental design are lacking, forcing researchers to risk costly demultiplexing failures. To address this, we introduce SNP-Information Content (SNP-IC) and cell-paird SNP-Information Content (cpSNP-IC), quantitative metrics that can be computed from simple, unpooled pilot data and that accurately predict the success of demultiplexing. oddSNP is an open-source framework for computing these metrics, enabling in-silico titration of sequencing depth and donor complexity to optimize experimental design before committing to large-scale studies.

Details on these metrics and the implementation of the tool are available in the manuscript entitled: OddSNP: a predictive framework for optimizing multiplexed single-cell RNA-seq (https://doi.org/10.64898/2025.12.08.692882).

oddSNP is developed at the Nemoto-lab, The University of Osaka.

The full documentation of oddSNP is available at: https://nemoto-lab.github.io/oddSNP/

The recommended way to install oddSNP is by using a virtual environments manager such as Conda (or venv).

We create a new conda environment and directly install oddSNP from its bioconda source.

:~$ conda create --name oddsnp python=3.12
:~$ conda activate oddsnp
(oddsnp):~$ conda install -c bioconda oddsnp

Still, we recommend to install oddSNP inside a virtual environment. In this case, we need to make sure to also install pip to the created environment to avoid interfering with system libraries.

:~$ conda create --name oddsnp python=3.12
:~$ conda activate oddsnp
(oddsnp):~$ conda install pip
(oddsnp):~$ pip install oddsnp

Details on how to install oddSNP from source are given in the Tutorial notebook.

An installation of cellsnp-lite is required to perform pileup calculations within oddSNP. To install it, use the following command inside your activated conda environment:

(oddsnp):~$ conda install -c bioconda cellsnp-lite 

NOTE Other installation methods for cellsnp-lite are described in their original website.

To check the installation finished properly, we can try and run oddSNP from the command line without any sub-commands. The output should be as follows:

(oddsnp):~$ oddSNP 
Usage: oddSNP [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  cpsnpic
  downsample
  genotype
  snpic
  utils

For details on how to use oddSNP please refer to the accompanying tutorial notebook: tutorial.ipynb

If you use this repository in your research, please cite our bioRxiv preprint:

OddSNP: a predictive framework for optimizing multiplexed single-cell RNA sequencing
Allendes Osorio, R.S., Nishimura, T., Shigihara, Y., Kimura, M., Takebe, T. and Nemoto, T. (2025)
https://www.biorxiv.org/content/10.64898/2025.12.08.692882v1

@article{osorio2025oddsnp,
  title   = {OddSNP: a predictive framework for optimizing multiplexed single-cell RNA sequencing},
  author  = {Allendes Osorio, R.S. and Nishimura, T. and Shigihara, Y. and Kimura, M. and Takebe, T. and Nemoto, T.},
  journal = {bioRxiv},
  year    = {2025},
  doi     = {10.64898/2025.12.08.692882},
  url     = {https://www.biorxiv.org/content/10.64898/2025.12.08.692882v1},
  note    = {Preprint}
}