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A simple python package for doublet detection in scRNA-seq data

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SoCube

license python torch docker pypi pmid SoCube Workflow

Introduction

SoCube is an end-to-end doublet detection tool with novel feature embedding strategy. User manual is published on this repo's github page.

Installment

You can just install socube by executing pip command.

pip install socube

For install detail, please see at user manual.

Usage

The basic usage of socube with gpus is as follows.

socube -i data/pbmc-1C-dm.h5ad --gpu-ids 0

Please visit our user manual for usage detail.

Paper reproduce

This repo is open source for socube software. If you want reprocduce result in original paper, Please visit repo GCS-ZHN/socube-reproduce.

Help

Any problem, you could create an issue, we will receive an email sent by github and reply it as soon as possible.

Citation

If you used our software, please cite it.

@article{10.1093/bib/bbad104,
    author = {Zhang, Hongning and Lu, Mingkun and Lin, Gaole and Zheng, Lingyan and Zhang, Wei and Xu, Zhijian and Zhu, Feng},
    title = "{SoCube: an innovative end-to-end doublet detection algorithm for analyzing scRNA-seq data}",
    journal = {Briefings in Bioinformatics},
    year = {2023},
    month = {03},
    abstract = "{Doublets formed during single-cell RNA sequencing (scRNA-seq) severely affect downstream studies, such as differentially expressed gene analysis and cell trajectory inference, and limit the cellular throughput of scRNA-seq. Several doublet detection algorithms are currently available, but their generalization performance could be further improved due to the lack of effective feature-embedding strategies with suitable model architectures. Therefore, SoCube, a novel deep learning algorithm, was developed to precisely detect doublets in various types of scRNA-seq data. SoCube (i) proposed a novel 3D composite feature-embedding strategy that embedded latent gene information and (ii) constructed a multikernel, multichannel CNN-ensembled architecture in conjunction with the feature-embedding strategy. With its excellent performance on benchmark evaluation and several downstream tasks, it is expected to be a powerful algorithm to detect and remove doublets in scRNA-seq data. SoCube is freely provided as an end-to-end tool on the Python official package site PyPi (https://pypi.org/project/socube/) and open-source on GitHub (https://github.com/idrblab/socube/).}",
    issn = {1477-4054},
    doi = {10.1093/bib/bbad104},
    url = {https://doi.org/10.1093/bib/bbad104},
    note = {bbad104},
    eprint = {https://academic.oup.com/bib/advance-article-pdf/doi/10.1093/bib/bbad104/49570241/bbad104.pdf},
}