학부 소식

프린트 링크

제목 - 설명
김준일 교수, Bioinformatics에 논문 게재 등록일 2021.05.13 조회수 1434 첨부파일 VeTra-a-tool-for-trajectory-inference-based-on-RNA-velocity.pdf
VeTra: a tool for trajectory inference based on RNA velocity Guangzheng Weng, Junil Kim, Kyoung Jae Won Abstract Motivation Trajectory inference (TI) for single cell RNA sequencing (scRNAseq) data is a powerful approach to interpret dynamic cellular processes such as cell cycle and development. Still, however, accurate inference of trajectory is challenging. Recent development of RNA velocity provides an approach to visualize cell state transition without relying on prior knowledge. Results To perform TI and group cells based on RNA velocity we developed VeTra. By applying cosine similarity and merging weakly connected components, VeTra identifies cell groups from the direction of cell transition. Besides, VeTra suggests key regulators from the inferred trajectory. VeTra is a useful tool for TI and subsequent analysis. Availability The Vetra is available at https://github.com/wgzgithub/VeTra. Supplementary information Supplementary data are available at Bioinformatics online. Issue Section: Original Paper URL: VeTra: a tool for trajectory inference based on RNA velocity \| Bioinformatics \| Oxford Academic (oup.com)

VeTra: a tool for trajectory inference based on RNA velocity