TIPS: trajectory inference of pathway significance through pseudotime comparison for functional assessment of single-cell RNAseq data.
TIPS: trajectory inference of pathway significance through pseudotime comparison for functional assessment of single-cell RNAseq data.
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DOI：
10.1093/bib/bbab124
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发表时间：
2021-09-02
影响因子：
9.5
通讯作者：
Ni Q
中科院分区：
文献类型：
--
作者：
Zheng Z;Qiu X;Wu H;Chang L;Tang X;Zou L;Li J;Wu Y;Zhou J;Jiang S;Wan Y;Ni Q
Recent advances in bioinformatics analyses have led to the development of novel tools enabling the capture and trajectory mapping of single-cell RNA sequencing (scRNAseq) data. However, there is a lack of methods to assess the contributions of biological pathways and transcription factors to an overall developmental trajectory mapped from scRNAseq data. In this manuscript, we present a simplified approach for trajectory inference of pathway significance (TIPS) that leverages existing knowledgebases of functional pathways and other gene lists to provide further mechanistic insights into a biological process. TIPS identifies key pathways which contribute to a process of interest, as well as the individual genes that best reflect these changes. TIPS also provides insight into the relative timing of pathway changes, as well as a suite of visualizations to enable simplified data interpretation of scRNAseq libraries generated using a wide range of techniques. The TIPS package can be run through either a web server or downloaded as a user-friendly GUI run in R, and may serve as a useful tool to help biologists perform deeper functional analyses and visualization of their single-cell data.
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