Author

Xi Xi

Tsinghua UniversityORCID 0000-0002-9207-1804Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:scRNA-seq· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Research Focus:eQTL / molecular QTL mapping· 1 Organism:human· 1 Assay:scATAC-seq· 1

Frequent Co-Authors

Xuegong ZhangiD· 3 shared Jiaqi LiiD· 2 shared Lei WeiiD· 2 shared Qiuchen MengiD· 2 shared Rui JiangiD· 2 shared Sijie CheniD· 2 shared Xiaowo WangiD· 2 shared Catherine Zhang· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 43 mutual co-author links

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3 shared papersBioinformatics

Xuegong ZhangORCID

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3 papers

Recent·Most cited

A generic reference defined by consensus peaks for scATAC-seq data analysis

Qiuchen Meng, Xinze Wu, Wen‐Chang Chen, Yubo Zhao, Chen Li, Wei Zheng, Jiaqi Li, Xi Xi, Sijie Chen, Catherine Zhang, Shengquan Chen, Jiaqi Li, Xiaowo Wang, Rui Jiang, Lei Wei, Xuegong Zhang

The paper constructs a generic chromatin accessibility reference (cPeaks) from bulk ATAC-seq data to improve scATAC-seq analysis and cell type identification.

bioRxiv · May 30, 2023 · PreprintBioinformatics

hECA: the cell-centric assembly of a cell atlas

Sijie Chen, Yanting Luo, Haoxiang Gao, Fanhong Li, Yixin Chen, Jiaqi Li, Renke You, Minsheng Hao, Haiyang Bian, Xi Xi, Wenrui Li, Weiyu Li, Mingli Ye, Qiuchen Meng, Ziheng Zou, , Xuegong Zhang

The paper introduces hECA, a cell-centric human Ensemble Cell Atlas, which integrates scRNA-seq data from multiple studies to enable targeted data retrieval, multi-view presentations, and customizable reference creation for cell type annotations.

iScience · Apr 28, 2022Peer-reviewedBioinformatics

SCeQTL: an R package for identifying eQTL from single-cell parallel sequencing data

Yue Hu, Xi Xi, Qian Yang, Xuegong Zhang

SCeQTL is an R package that identifies eQTL from single-cell sequencing data using zero-inflated negative binomial regression to detect gene-expression differences across genotype groups and other factors.

BMC Bioinformatics · May 11, 2020Peer-reviewedBioinformatics