单细胞测序数据分析

 

项目支持

Ø  国家自然科学基金重点项目:面向单细胞RNA测序数据的深度迁移模型与细胞通信网络研究(62131004

Ø  国家自然科学基金面上项目:基于植物单细胞转录组和多组学数据分析及基因调控网络构建方法的研究(62272321

Ø  国家自然科学基金面上项目:基于单细胞多组学数据的细胞-药物反应预测深度强化学习模型的构建与研究(62372332

Ø  国家自然科学基金青年基金项目:大型单细胞转录组数据降维与可视化(62102064

Ø  国家自然科学基金青年基金项目:基于单细胞测序数据的药物反应预测研究(62201129

Ø  国家自然科学基金青年基金项目:面向单细胞多组学数据的癌症基因调控网络预测(62301369

Ø  国家自然科学基金地区基金项目:单细胞转录组与空间转录组数据整合方法研究(62261018

成员

邹权 (教授,电子科大)

魏乐义(教授,山东大学)

张子龙 (副教授,海南大学)

张永清 (副教授,成都信息工程大学)

齐忍(博士后,电子科大)

王嘉程(博士生,电子科大)

刘怡(博士生,电子科大)

钱昱罄(博士生,电子科大)

焦仕虎(科研助理,电子科大)

网站服务或数据库

webSCST: an interactive web application for single-cell RNA-seq data and spatial transcriptome data integration

scIMC: a platform for benchmarking comparison and visualization analysis of scRNA-seq data imputation methods

组织专刊

Machine Learning Methods in Single-Cell Immune and Drug Response Prediction in Frontiers of Genetics

发表论文

1.         Ziwei Wang, Hui Ding, Quan Zou*. Identifying Cell Types to Interpret scRNA-seq Data: How, Why, and More Possibilities. Briefings in Functional Genomics. 2020, 19(4):286-291

2.        Ren Qi, Anjun Ma, Qin Ma*, Quan Zou*. Clustering and Classification Methods for Single-cell RNA-sequencing Data. Briefings in Bioinformatics. 2020, 21(4): 1196-1208.

3.        Ziwei Wang, Chi-chang Chang*, Quan Zou*. COVID-19 Related Research by Data Mining in Single Cell Transcriptome Profiles. Journal of Electronic Science and Technology. 2021, 19(1):1-5

4.        Ren Qi, Jin Wu, Fei Guo, Lei Xu*, Quan Zou*. A Spectral Clustering with Self-weighted Multiple Kernel Learning Method for single-cell RNA-seq Data. Briefings in Bioinformatics. 2021, 22(4): bbaa216. (Codes)

5.         Zilong Zhang, Feifei Cui, Chunyu Wang, Lingling Zhao*, Quan Zou*. Goals and Approaches for Each Processing Step for Single-Cell RNA Sequencing Data. Briefings in Bioinformatics. 2021, 22(4): bbaa314. (codes)

6.        Zilong Zhang, Feifei Cui, Chen Lin, Lingling Zhao, Chunyu Wang*, Quan Zou*. Critical downstream analysis steps for single-cell RNA sequencing data. Briefings in Bioinformatics. 2021,22(5):bbab105. (codes)

7.         Zilong Zhang, Feifei Cui, Murong Zhou, Song Wu*, Quan Zou*, Bo Gao*. Single-cell RNA sequencing analysis identifies key genes in brain metastasis from lung adenocarcinoma. Current gene therapy. 2021, 21(4): 338-348

8.        Zilong Zhang, Feifei Cui, Chen Cao, Qingsuo Wang*, Quan Zou*. Single-cell RNA analysis reveals the potential risk of organ-specific cell types vulnerable to SARS-CoV-2 infections. Computers in Biology and Medicine. 2022, 140: 105092

9.        Jiacheng Wang, Quan Zou*, Chen Lin*. A comparison of deep learning-based pre-processing and clustering approaches for single-cell RNA sequencing data. Briefings in Bioinformatics. 2022, 23(1): bbab345

10.     Ziwei Wang, Ying Zhang, Qun Li, Quan Zou*, Qing Liu*. A road map for happiness: The psychological factors related cell types in various parts of human body from single cell RNA-seq data analysis. Computers in Biology and Medicine. 2022, 143:105286

11.      Mengyuan Zhao, Wenying He, Jijun Tang*, Quan Zou*, Fei Guo*. A hybrid deep learning framework for gene regulatory network inference from single-cell transcriptomic data. Briefings in Bioinformatics. 2022, 23(2): bbab568

12.     Zilong Zhang, Feifei Cui, Wei Su, Lijun Dou, Anqi Xu, Chen Cao, Quan Zou*. webSCST: an interactive web application for single-cell RNA-sequencing data and spatial transcriptomic data integration. Bioinformatics. 2022, 38(13):3488-3489. (web server)

13.     Chichi Dai, Yi Jiang, Chenglin Yin, Ran Su, Xiangxiang Zeng, Quan Zou, Kenta Nakai*, Leyi Wei*. scIMC: a platform for benchmarking comparison and visualization analysis of scRNA-seq data imputation methods. Nucleic Acids Research. 2022, 50(9):4877-4899. (web server)

14.     Yongqing Zhang, Maocheng Wang, Zixuan Wang, Yuhang Liu, Shuwen Xiong, Quan Zou*. MetaSEM: Gene regulatory network inference from single-cell RNA data by Meta-learning. International Journal of Molecular Sciences. 2023, 24: 2595

15.      Ren Qi, Quan Zou*. Trends and Potential of Machine Learning and Deep Learning in Drug Study at Single-cell Level. Research. 2023, 6: 0050

16.     Jing Jiang, Junlin Xu, Yuansheng Liu, Bosheng Song, Xiulan Guo, Xiangxiang Zeng, Quan Zou*. Dimensionality reduction and visualization of single-cell RNA-seq data with an improved deep variational autoencoder. Briefings in Bioinformatics. 2023, 24(3): bbad152. (codes)

17.      Yushan Qiu, Chang Yan, Pu Zhao, Quan Zou*. SSNMDI: a novel joint learning model of semi-supervised non-negative matrix factorization and data imputation for clustering of single-cell RNA-seq data. Briefings in Bioinformatics. 2023, 24(3): bbad149

18.     Zixuan Wang, Yongqing Zhang, Yun Yu, Junming Zhang, Yuhang Liu, Quan Zou*.  Single-cell ATAC-seq analysis by Transformer-based cell embedding. International Journal of Molecular Sciences. 2023, 24(5): 4784

19.     Jiacheng Wang, Yaojia Chen, Quan Zou*. Inferring gene regulatory network from single-cell transcriptomes with graph autoencoder model. PLoS Genetics. 2023, 19(9): e1010942 (codes)

20.    Ren Qi, Quan Zou*. Editorial: Machine Learning Methods in Single-Cell Immune and Drug Response Prediction. Frontiers in Genetics. 2023, 19: 1233078

21.     Chaorui Yan, Yanxu Zhu, Miao Chen, Kainan Yang, Feifei Cui*, Quan Zou*, Zilong Zhang*. Integration tools for scRNA-seq data and spatial transcriptomics sequencing data. Briefings in Functional Genomics. Doi: 10.1093/bfgp/elae002

22.     Yushan Qiu, Lingfei Yang, Hao Jiang*, Quan Zou*. scTPC: a novel semi-supervised deep clustering model for scRNA-seq data. Bioinformatics. 2024, 40(5): btae293 (codes)

23.     Yushan Qiu, Dong Guo, Pu Zhao, Quan Zou*. scMNMF: a novel method for single-cell multi-omics clustering based on matrix factorization. Briefings in Bioinformatics. 2024, 25(3): bbae228. (codes)