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/
Installation
The recommended way to install oddSNP is by using a virtual environments manager such as Conda (or venv).
Using Bioconda:
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
Using PyPI:
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
From source:
Details on how to install oddSNP from source are given in the Tutorial notebook.
After installation
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
Using oddSNP
For details on how to use oddSNP please refer to the accompanying tutorial notebook: tutorial.ipynb
📄 How to Cite
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
BibTeX
@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}
}
Metadata
Release files for oddSNP 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| oddsnp-0.1.2.tar.gz | 21.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| oddsnp-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 47.4 kB
Release files / oddsnp-0.1.2.tar.gz
| Download URL | oddsnp-0.1.2.tar.gz |
|---|---|
| Size | 21.8 kB |
| Tags | Source |
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| Download URL | oddsnp-0.1.2-py3-none-any.whl |
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| Tags | Python 3 |
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| Uploaded via |
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