seneR: An R package for comprehensive senescence assessment and its application in type 2 diabetes and osteoarthritis.

Yi Zhang, Xinming Zhang, Cheng Chen, Bing Li, Yao Lu, Xin Ma, Yunfeng Yang

Department of Orthopedics, Tongji Hospital, School of Medicine, Tongji University, Shanghai 200092, China.Department of Orthopedics, Tongji Hospital, School of Medicine, Tongji University, Shanghai 200092, China. · pubmed

Paper

Abstract

Cellular senescence is a key driver of aging and chronic diseases. However, accurately identifying senescent cells is challenging due to limitations of conventional biomarkers and senescence heterogeneity. Transcriptome-wide analyses offer powerful tools for deciphering cellular states. Yet, there is a critical gap in computational frameworks for senescence assessment from transcriptomic data.

The following analysis is generated by AI and may contain errors. It is separate from the authors’ abstract and is not peer review.

Research summary

The paper presents a new R package for assessing cellular senescence using transcriptomic data. This research is relevant as it addresses a fundamental aspect of aging and chronic diseases by improving the identification of senescent cells, which are key contributors to the aging process.

Author of this paper? Send a correction.