Author

Qingshan Ni

Army Medical UniversityORCID 0000-0002-7267-8932Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Assay:scRNA-seq· 2 Research Focus:trajectory inference· 2 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Haiyang WuiD· 2 shared Jianzhi Zhou· 2 shared Liyun ZouiD· 2 shared Xiangyu TangiD· 2 shared Ying WaniD· 2 shared Zihan ZhengiD· 2 shared Fa Xu· 1 shared Gang CheniD· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Haiyang WuORCID

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Author profile →

2 papers

Recent·Most cited

TIPS: Trajectory Inference of Pathway Significance through Pseudotime Comparison for Functional Assessment of single-cell RNAseq Data

Zihan Zheng, X. Qiu, Haiyang Wu, Ling Chang, Xiangyu Tang, Liyun Zou, Jingyi Li, Yuzhang Wu, Jianzhi Zhou, Shan Jiang, Ying Wan, Qingshan Ni

TIPS assesses pathway and transcription factor contributions to developmental trajectories in scRNAseq data through pseudotime comparison and provides visualization tools.

Briefings in Bioinformatics · Mar 18, 2021Peer-reviewedBioinformatics

scSTATseq: Diminishing Technical Dropout Enables Core Transcriptome Recovery and Comprehensive Single-cell Trajectory Mapping

Zihan Zheng, Xiangyu Tang, Xin Qiu, Hao Xu, Haiyang Wu, Haili Yu, Xingzhao Wen, Zhou Peng, Fa Xu, Yiwen Zhou, Qingshan Ni, Jianzhi Zhou, Liyun Zou, Gang Chen, Ying Wan

scSTATseq reduces technical dropout in scRNA-seq, enabling comprehensive transcriptome recovery and trajectory mapping, as demonstrated in osteoclast differentiation analysis.

bioRxiv · Apr 15, 2020 · PreprintGenomics