TIPS: trajectory inference of pathway significance through pseudotime comparison for functional assessment of single-cell RNAseq data.

ABSTRACT: 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 tim

SUBMITTER: Zheng Z 

PROVIDER: S-EPMC8425418 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature